Age-related cognitive impairments are observed across multiple species, including laboratory rodents and humans. Forms of learning that require an intact hippocampal formation, such as spatial navigation, are severely impacted in aged humans (Etchamendy et al., 2012), rats (Gallagher and Pelleymounter, 1988), and mice (Bach et al., 1999). Although age-related cognitive deficits have been observed across numerous tasks and species, not all aged subjects display these impairments (Gallagher and Pelleymounter, 1988; Knuttinen et al., 2001a, 2001b). Therefore, the aging population can be split into aged individuals who are cognitively-impaired, and others who are cognitively-unimpaired. These cognitively-unimpaired ‘super agers’ are capable of learning and remembering at young-like levels (Curlik et al., 2014; Gallagher and Pelleymounter, 1988; Knuttinen et al., 2001a; Rogalski et al., 2013).

Identifying the molecular mechanisms that differentiate successful from unsuccessful cognitive-agers is highly desirable, as knowledge of the underlying mechanisms will greatly facilitate treatment of these impairments. One likely mechanism contributing to age-related cognitive deficits is a decrease in the intrinsic excitability of CA1 pyramidal neurons. Numerous studies have revealed that CA1 pyramidal neurons from aged animals have reduced intrinsic excitability when compared to those from young animals. Specifically, pyramidal neurons from area CA1 of the dorsal hippocampus of aged animals exhibit a larger post-burst afterhyperpolarization (AHP) than those from young animals (Disterhoft and Oh, 2007, 2006; Gant et al., 2006; Landfield and Pitler, 1984; Oh et al., 2013). The magnitude of this age-related decrease in neuronal excitability correlates with age-related cognitive deficits (Tombaugh et al., 2005). Aged impaired (AI) animals have larger AHPs than both young animals, and aged unimpaired (AU) animals. Interestingly, the AHP amplitude from AU animals is no different than that of young animals (Matthews et al., 2009; Moyer et al., 2000; Tombaugh et al., 2005). Moreover, pharmacological compounds that reduce the amplitude of the AHP in vitro, ameliorate age-related cognitive impairments in vivo (Kronforst-Collins et al., 1997; Moyer et al., 1992; Oh et al., 1999). Based on these findings, we are searching for molecular pathway(s) that modulate both cognition and intrinsic cellular excitability.

One such pathway is activated by the transcription factor, cAMP response element-binding protein (CREB; (Alberini, 2009). Numerous studies have manipulated CREB activation in young animals to demonstrate its essential role in memory formation (Bernabeu et al., 1997; Bourtchuladze et al., 1994; Dash et al., 1990; Deisseroth et al., 1998; Kaang et al., 1993). Memories for spatial and cued information were impaired in transgenic mice expressing a dominant negative form of CREB (Pittenger et al., 2002). Likewise, mutations which prevent CREB from being activated by inhibiting its phosphorylation also impaired memory (Kida et al., 2002). Conversely, increases in CREB activity via transgenic or viral means facilitated memory. For instance, expressing a partially-active form of CREB (VP16-CREB) in the amygdala resulted in stronger memories for contextual and cued fear conditioning (Viosca et al., 2009b). Likewise, infusion of HSV-CREB into hippocampus or amygdala, results in CREB overexpression and facilitation of memory for the Morris water maze (Sekeres et al., 2010), water cross maze (Brightwell et al., 2007), or fear conditioning (Josselyn et al., 2001) in young animals.

Notably, manipulations that increase CREB activity in young animals have also been found to increase intrinsic excitability of their neurons. For example, expression of VP16-CREB resulted in increased neuronal excitability of numerous brain regions, including CA1 of hippocampus, the locus coeruleus, the nucleus accumbens, and the amygdala (Dong et al., 2006; Han et al., 2006; Lopez de Armentia et al., 2007; Viosca et al., 2009b). Moreover, overexpression of wild-type CREB has also been shown to be sufficient to enhance excitability (Yiu et al., 2011; Zhou et al., 2009). Taken together, these previous studies in young adult animals indicate that increasing CREB activity facilitates memory and increases intrinsic neuronal excitability.

Contrary to young adults, very little is known about age-related changes to hippocampal CREB levels and/or activity. Furthermore, the few published studies which have examined CREB levels in aging appear to present conflicting results. One study reported that levels of total CREB protein were unchanged with aging, however, levels of CREB phosphorylated at S133 (pCREB) decreased with age (Foster et al., 2001). Another study reported a decrease in total CREB with aging, which was specifically observed in aged animals that had impairments in spatial memory (Brightwell et al., 2004). A third study found that total CREB was unchanged, while pCREB increased with age (Monti et al., 2005). While the exact nature of age-related CREB levels is unclear, these findings do suggest that CREB levels in the hippocampal formation change with age. Additionally, upstream activators of CREB, such as cAMP, have been found to be decreased with age (Bach et al., 1999). Activation of protein kinase A, the next step in this activation cascade, is required for the learning-induced reduction in post-burst AHPs (Oh et al., 2009; Zhang et al., 2013), and reduced in aged rats (Karege et al., 2001). Calcineurin, a phosphatase that dephosphorylates CREB, has also been found to be increased with age (Foster et al., 2001). All of these factors could result in a decrease in CREB activation, which led us to hypothesize that increasing CREB levels would ameliorate both the cognitive and biophysical deficits observed in normal aging subjects. We tested this hypothesis by using an adeno-associated viral vector to overexpress wild-type rat CREB in CA1 of dorsal hippocampus. Spatial learning and memory were then assessed using two different Morris water maze protocols; a less challenging version, and a more difficult version. Our results revealed that CREB overexpression in dorsal CA1 ameliorated age-related long-term biophysical and behavioral deficits.

This is the first study to directly increase CREB levels in aged animals, and as a result, rescue their age-related cognitive deficits. Administration of AAV-CREB resulted in widespread infection of dorsal CA1 in young and aged rats, which specifically increased CREB mRNA levels in dorsal CA1. Importantly, this increase in CREB was sufficient to ameliorate age-related long-term spatial memory deficits. Furthermore, as predicted, aged pyramidal neurons infected by AAV-CREB had reduced post-burst AHPs, indicating that infected cells were more excitable. These data reaffirm that aging-related processes increase the AHP in CA1 neurons, and leads to decreased excitability that contributes to memory impairment. Increasing CREB levels is sufficient to reverse these processes and normalize memory function. Our data is clear, and is consistent with some previously reported work. However, it is at odds with other reports, and we suspect that a number of different experimental variables contribute to this inconsistency in the literature.

Aged animals, as a group, displayed robust spatial memory deficits. However, not every aged animal was impaired. Nearly all aged CREB animals, and a subset of aged GFP rats were able to learn and remember both the less challenging, and more difficult task at young-like levels. These results are consistent with those of earlier studies, indicating that approximately half of aged rats are impaired on this task (Disterhoft and Oh, 2006; Gallagher et al., 1993). With that said, our aged control animals could be separated into those with impaired long-term spatial memory, and those without impaired long-term spatial memory, whereas aged animals receiving AAV-CREB were much more homogenous, consistently performing at, or near, young-like levels. We found water maze performance by our young and, presumably AU animals were not improved with AAV-CREB, which is supported by results of a prior study which revealed that viral administration of CREB-Y134F improved fear memory in young ‘poor learners’, with no improvement in young ‘good-learners’ (Cowansage et al., 2013). These findings are also supported by a study by Brightwell et al. (2004), which found that AI animals trained on water maze had lower levels of CREB protein than young animals and AU animals (2004). Together, these previous findings and our present results suggest that lower levels of CREB protein in AI animals contributes to their cognitive deficits, and increasing CREB in these animals can rescue their behavioral deficits. This rescue by CREB overexpression was most likely mediated by increased levels of pCREB. Despite reports of decreased CREB activation with aging, via increases in calcineurin (Foster et al., 2001) and decreases in PKA (Karege et al., 2001), we hypothesize that increasing the absolute levels of their substrate, CREB, would lead to an increase in the levels of pCREB and CREB activity. However, the detailed mechanistic relationship between the levels of CREB, pCREB, and CREB activity is unlikely to be straight forward (Briand et al., 2015).

A second parameter that might contribute to experimental variability is the nature of the CREB protein that is overexpressed. We found that CREB overexpression increased the intrinsic excitability of aged CA1 neurons. The AHPs from AAV-CREB infected neurons were reduced when compared to neighboring uninfected cells, or GFP-injected controls, as previously reported (Yiu et al., 2011; Zhou et al., 2009). These results mirror those from studies using pharmacological methods where treatment that reduced the AHP also facilitated cognitive performance in aged animals (Deyo et al., 1989; Kronforst-Collins et al., 1997; Moyer et al., 1992; Oh et al., 1999; Weible et al., 2004). Interestingly, we found that CREB overexpression had no observable effect on the size of AHPs in young neurons. Previous studies using partially-active CREB-Y134F or VP16-CREB have demonstrated their ability to facilitate long-term potentiation and reduce the AHP in cells from young animals (Lopez de Armentia et al., 2007; Suzuki et al., 2011; Yu et al., 2016). The increase in downstream transcription is likely to be much greater when a partially activated form of CREB, as opposed to wild-type, is used. This may in part explain why we did not see any effect of virus on AHP amplitude in cells from young animals.

A third variable is the excitability state of the animal at the time of training. Studies using CREB overexpression in young animals have produced mixed results. Zhou et al. (2009) used HSV-CREB to overexpress CREB in amygdala of mice, which resulted in a smaller AHP amplitude when measured 300 ms after the final action potential, as compared to neighboring control cells. Peak AHP was not found to be different (2009). Another study transfected primary mice hippocampal neurons to overexpress CREB and found that transfected cells had increased excitability (Yiu et al., 2014). Lastly, when HSV-CREB was injected into locus coeruleus of rats, excitability was unchanged, as compared to rats injected with control virus (Han et al., 2006). These varying results may be due to differences in slice vs. cultured neurons, mouse vs. rat tissue, or even due to differing brain regions, but we suspect that the ‘excitability state’ of the animals is a major uncontrolled determinant. In our hands, CREB overexpression was not sufficient to cause any differences in peak or slow AHP amplitude in CA1 neurons from young animals. Although we saw similar levels of CREB overexpression in both age groups, only the aged animals exhibited a change at the biophysical level. It is possible that while the young animals are already at an ‘optimal state’, and have sufficient excitability or plasticity for learning and memory, the aged animals are in a ‘sub-optimal state’, and therefore have room for improvement. This effect has been demonstrated before, where systemic application of L-type calcium channel blocker nimodipine (Deyo et al., 1989) or cholinesterase inhibitor galantamine (Weible et al., 2004) was beneficial for aged animals, but had no effect on young. Similarly, exposure to environmental enrichment, which can indirectly lead to increased CREB activation (Hu et al., 2013), reduced the AHP in neurons from aged animals, but not young (Kumar and Foster, 2007). For potential therapeutic purposes, this may be a desirable trait, so as to only affect those who have room for improvement.

Given our biophysical results, it is not surprising that AAV-CREB (vs. AAV-GFP) injections had no effect on any aspect of young animals’ water maze performance. We have demonstrated that viral overexpression of CREB was achieved in these young animals, both at the mRNA and protein levels. Overexpression of wild-type rat CREB, as opposed to a mutated form of CREB, may partly explain the lack of behavioral effect. Expression of VP16-CREB in young animals has led to transient facilitation of eye-blink conditioning (Gruart et al., 2012), as well as facilitation of memory for contextual and cued fear (Viosca et al., 2009a). Additionally, expression of a CREB-Y134F in young animals has given enhanced memory for both fear conditioning and water maze (Restivo et al., 2009; Suzuki et al., 2011). These studies suggest that the increase in CREB expression we observed with our AAV-CREB was not sufficient (when compared to that achieved by mutated forms of CREB) to facilitate the behavioral performance of young animals. However, some studies have shown facilitation of fear conditioning as a result of HSV overexpression of wild-type CREB in the amygdala (Josselyn et al., 2001; Sekeres et al., 2010). In these studies, animals underwent weak training, where control animals failed to form a memory, but animals overexpressing CREB were able to do so. In the current study, we initially used a less challenging version of the water maze task, and delivered 4 sessions of training with five trials per session. We suspected this ‘strong’ training may have produced a ceiling effect in our young animals, where increasing CREB activity could not lead to further improvements. Thus, we injected a new group of animals with AAV-GFP and AAV-CREB, and trained them on a more difficult version of the task, to determine if young CREB animals’ performance would then be facilitated. The difficult version did prove more challenging, with both young and aged animals taking longer to learn the task, and spending less time in the target quadrant across probe trials as compared to the less challenging version. Interestingly, the pattern of behavioral results was very similar to that observed during the less challenging task: CREB mediated rescue in aged rats, but had no effect in young rats. This suggests that the difference between the viral overexpression of HSV and AAV may be at play. HSV is known to give strong, but transient gene expression, while AAV tends to provide more subtle, but stable expression over long periods of time (Neve et al., 2005). These data indicate that strong CREB overexpression, such as in the case of HSV, or a mutant form of CREB is required to achieve behavioral facilitation in young adult animals, given that they are already at an ‘optimal learning state’.

Notably, CREB mRNA levels were not related to behavioral performance. Young GFP and CREB groups whose behavior did not differ showed differing CREB mRNA levels; while AU and AI groups, who by definition differ in behavior, had the same levels of CREB mRNA. However, levels of CREB protein and pCREB have repeatedly been shown to be related to behavior (Brightwell et al., 2004; Cowansage et al., 2013; Josselyn et al., 2001; Pittenger et al., 2002; Viosca et al., 2009a). Importantly, we provide evidence that basal level of CREB protein is correlated to successful learning in aged rats (Figure 3—figure supplement 2). Together, these findings suggest that CREB mRNA and protein levels are not directly related to each other. Moreover, while CREB mRNA levels served to confirm viral overexpression, only CREB protein levels were predictive of behavioral performance.

Interestingly, CREB mRNA levels did not differ between young and aged animals in CA1, but it was reduced in DG of aged animals. While this is an important observation, given the lack of relationship between CA1 CREB mRNA levels and behavior, our focus continues to be on the CA1 sub-region. We chose to target this sub-region of the hippocampus as it has exhibited biophysical deficits with age (Bach et al., 1999; Disterhoft and Oh, 2007; Tombaugh et al., 2005). Additionally, CA1 has been targeted to successfully facilitate memory in young animals with CREB overexpression (Sekeres et al., 2010). In our present study, targeting the CA1 sub-region has successfully enhanced intrinsic excitability of aged pyramidal neurons, with a corresponding amelioration of age-related memory deficits.

The postburst AHP is influenced by numerous manipulations. One of these is successful learning of a behavioral task, where animals that learn exhibit smaller AHPs than those who do not (Oh and Disterhoft, 2015; Moyer et al., 1996). However, the learning-related reduction in postburst AHP is transient, and AHP amplitudes return to baseline within two weeks after the end of behavioral training (Moyer et al., 1996; Thompson et al., 1996; Tombaugh et al., 2005). All biophysical recordings in this study were made between two to three weeks after the end of behavioral testing in order to measure the baseline AHP, and to avoid any learning-induced changes in the AHP. However, this still raises the question of how CREB overexpression resulted in the reduction of the AHP. CREB may modulate the AHP by indirectly influencing the levels or activity of AHP channels via one or more of CREB’s downstream transcriptional targets. Alternatively, it is possible that CREB could act on AHP channels via a previously unknown non-transcriptional mechanism. Elucidating this mechanism would be of great interest. Despite not fully understanding the mechanisms involved, the consequences of CREB’s enhancement of neuronal excitability have been examined. Neurons that have increased CREB activity become more excitable (Lopez de Armentia et al., 2007), and are then preferentially recruited to form new memories (Han et al., 2007; Yiu et al., 2014; Zhou et al., 2009).

While previous studies have manipulated factors upstream of CREB, such as cAMP levels (Bach et al., 1999), this is the first study to directly test CREB’s role in age-related cognitive deficits. Previous studies have shown increases in calcineurin with aging (Foster et al., 2001), decreases in PKA, (Foster et al., 2001; Karege et al., 2001), and AI animals have been shown to have reduced CREB protein (Brightwell et al., 2004). All of these could result in decreases in CREB function, but only one study has manipulated CREB levels with aging. Mouravlev et al. (2006) did a longitudinal study revealing that overexpressing wild-type CREB in young rats prevents age-related cognitive deficits from arising later in life. However, it was still unclear whether CREB would be able to reverse the age-related deficits after they arose. In our present study, CREB overexpression alone was sufficient to rescue the long-term memory deficits in aged animals. We hypothesize that CREB’s effects on behavioral performance may have been via the normalization of the previously reported deficits in CREB activity/function. This hypothesis is supported by our finding that CREB protein levels strongly correlate with performance on probe 4, where aged animals with the lowest levels of CREB protein performed the worst. This suggests that aged animals with low CREB protein levels are more likely to be AI. On the other hand, aged animals with high CREB protein levels, either naturally or due to AAV-CREB infusions, are more likely to perform at young-like levels. Alternatively, it is also possible that CREB overexpression may have compensated for age-related deficits via other mechanisms. Possibilities include CREB’s ability to modulate synaptic plasticity (Benito and Barco, 2010), and to induce preferential recruitment of neurons to form a new memory via increasing intrinsic excitability (Han et al., 2007; Yiu et al., 2014; Zhou et al., 2009).

In addition to these findings contributing to a better understanding of the aging process, other studies have shown that CREB and its activation are also negatively impacted in Alzheimer’s disease. Amyloid –beta treatment reduces CREB levels and can cause it to be retained in the cytoplasm (Arvanitis et al., 2007; Pugazhenthi et al., 2011), while high BACE-1 levels reduce CREB activation (Chen et al., 2012), and CREB-mediated gene expression is aberrant in brains of Alzheimer’s patients (Satoh et al., 2009). A recent study has also shown that Tau accumulation reduces CREB activity by increasing calcineurin levels (Yin et al., 2016). Together, these results suggest that impaired, or sub-optimal CREB function in aging may make aged individuals more vulnerable to Alzheimer’s disease. Furthermore, this indicates that CREB may not only be targeted for amelioration of cognitive deficits seen in normal aging, it could also be an important pharmacological target in the prevention or treatment of Alzheimer’s disease.

1. 1. Alberini CM

   (2009) Transcription factors in long-term memory and synaptic plasticity

   Physiological Reviews 89:121–145.

   https://doi.org/10.1152/physrev.00017.2008

   • PubMed
   • Google Scholar
2. 1. Arvanitis DN
   2. Ducatenzeiler A
   3. Ou JN
   4. Grodstein E
   5. Andrews SD
   6. Tendulkar SR
   7. Ribeiro-da-Silva A
   8. Szyf M
   9. Cuello AC

   (2007) High intracellular concentrations of amyloid-beta block nuclear translocation of phosphorylated CREB

   Journal of Neurochemistry 103:216–228.

   https://doi.org/10.1111/j.1471-4159.2007.04704.x

   • PubMed
   • Google Scholar
3. 1. Bach ME
   2. Barad M
   3. Son H
   4. Zhuo M
   5. Lu YF
   6. Shih R
   7. Mansuy I
   8. Hawkins RD
   9. Kandel ER

   (1999) Age-related defects in spatial memory are correlated with defects in the late phase of hippocampal long-term potentiation in vitro and are attenuated by drugs that enhance the cAMP signaling pathway

   PNAS 96:5280–5285.

   https://doi.org/10.1073/pnas.96.9.5280

   • PubMed
   • Google Scholar
4. 1. Benito E
   2. Barco A

   (2010) CREB's control of intrinsic and synaptic plasticity: implications for CREB-dependent memory models

   Trends in Neurosciences 33:230–240.

   https://doi.org/10.1016/j.tins.2010.02.001

   • Google Scholar
5. 1. Bernabeu R
   2. Bevilaqua L
   3. Ardenghi P
   4. Bromberg E
   5. Schmitz P
   6. Bianchin M
   7. Izquierdo I
   8. Medina JH

   (1997) Involvement of hippocampal cAMP/cAMP-dependent protein kinase signaling pathways in a late memory consolidation phase of aversively motivated learning in rats

   PNAS 94:7041–7046.

   https://doi.org/10.1073/pnas.94.13.7041

   • PubMed
   • Google Scholar
6. 1. Bourtchuladze R
   2. Frenguelli B
   3. Blendy J
   4. Cioffi D
   5. Schutz G
   6. Silva AJ

   (1994) Deficient long-term memory in mice with a targeted mutation of the cAMP-responsive element-binding protein

   Cell 79:59–68.

   https://doi.org/10.1016/0092-8674(94)90400-6

   • PubMed
   • Google Scholar
7. 1. Briand LA
   2. Lee BG
   3. Lelay J
   4. Kaestner KH
   5. Blendy JA

   (2015) Serine 133 phosphorylation is not required for hippocampal CREB-mediated transcription and behavior

   Learning & Memory 22:109–115.

   https://doi.org/10.1101/lm.037044.114

   • PubMed
   • Google Scholar
8. 1. Brightwell JJ
   2. Gallagher M
   3. Colombo PJ

   (2004) Hippocampal CREB1 but not CREB2 is decreased in aged rats with spatial memory impairments

   Neurobiology of Learning and Memory 81:19–26.

   https://doi.org/10.1016/j.nlm.2003.08.001

   • PubMed
   • Google Scholar
9. 1. Brightwell JJ
   2. Smith CA
   3. Neve RL
   4. Colombo PJ

   (2007) Long-term memory for place learning is facilitated by expression of cAMP response element-binding protein in the dorsal hippocampus

   Learning & Memory 14:195–199.

   https://doi.org/10.1101/lm.395407

   • PubMed
   • Google Scholar
10. 1. Chen Y
    2. Huang X
    3. Zhang YW
    4. Rockenstein E
    5. Bu G
    6. Golde TE
    7. Masliah E
    8. Xu H

    (2012) Alzheimer's β-secretase (BACE1) regulates the cAMP/PKA/CREB pathway independently of β-amyloid

    Journal of Neuroscience 32:11390–11395.

    https://doi.org/10.1523/JNEUROSCI.0757-12.2012

    • PubMed
    • Google Scholar
11. 1. Cowansage KK
    2. Bush DEA
    3. Josselyn SA
    4. Klann E
    5. LeDoux JE

    (2013) Basal variability in CREB phosphorylation predicts trait-like differences in amygdala-dependent memory

    PNAS 110:16645–16650.

    https://doi.org/10.1073/pnas.1304665110

    • Google Scholar
12. 1. Curlik DM
    2. Weiss C
    3. Nicholson DA
    4. Disterhoft JF

    (2014) Age-related impairments on one hippocampal-dependent task predict impairments on a subsequent hippocampal-dependent task

    Behavioral Neuroscience 128:676–688.

    https://doi.org/10.1037/bne0000018

    • PubMed
    • Google Scholar
13. 1. Dash PK
    2. Hochner B
    3. Kandel ER

    (1990) Injection of the cAMP-responsive element into the nucleus of aplysia sensory neurons blocks long-term facilitation

    Nature 345:718–721.

    https://doi.org/10.1038/345718a0

    • PubMed
    • Google Scholar
14. 1. Deisseroth K
    2. Heist EK
    3. Tsien RW

    (1998) Translocation of calmodulin to the nucleus supports CREB phosphorylation in hippocampal neurons

    Nature 392:198–202.

    https://doi.org/10.1038/32448

    • PubMed
    • Google Scholar
15. 1. Deyo RA
    2. Straube KT
    3. Disterhoft JF

    (1989) Nimodipine facilitates associative learning in aging rabbits

    Science 243:809–811.

    https://doi.org/10.1126/science.2916127

    • PubMed
    • Google Scholar
16. 1. Disterhoft JF
    2. Oh MM

    (2006) Learning, aging and intrinsic neuronal plasticity

    Trends in Neurosciences 29:587–599.

    https://doi.org/10.1016/j.tins.2006.08.005

    • PubMed
    • Google Scholar
17. 1. Disterhoft JF
    2. Oh MM

    (2007) Alterations in intrinsic neuronal excitability during normal aging

    Aging Cell 6:327–336.

    https://doi.org/10.1111/j.1474-9726.2007.00297.x

    • PubMed
    • Google Scholar
18. 1. Dong Y
    2. Green T
    3. Saal D
    4. Marie H
    5. Neve R
    6. Nestler EJ
    7. Malenka RC

    (2006) CREB modulates excitability of nucleus accumbens neurons

    Nature Neuroscience 9:475–477.

    https://doi.org/10.1038/nn1661

    • PubMed
    • Google Scholar
19. 1. Etchamendy N
    2. Konishi K
    3. Pike GB
    4. Marighetto A
    5. Bohbot VD

    (2012) Evidence for a virtual human analog of a rodent relational memory task: a study of aging and fMRI in young adults

    Hippocampus 22:869–880.

    https://doi.org/10.1002/hipo.20948

    • PubMed
    • Google Scholar
20. 1. Foster TC
    2. Sharrow KM
    3. Masse JR
    4. Norris CM
    5. Kumar A

    (2001)

    Calcineurin links Ca2+ dysregulation with brain aging

    Journal of Neuroscience  21:4066–4073.

    • PubMed
    • Google Scholar
21. 1. Foster TC

    (2012) Dissecting the age-related decline on spatial learning and memory tasks in rodent models: N-methyl-D-aspartate receptors and voltage-dependent Ca2+ channels in senescent synaptic plasticity

    Progress in Neurobiology 96:283–303.

    https://doi.org/10.1016/j.pneurobio.2012.01.007

    • PubMed
    • Google Scholar
22. 1. Gallagher M
    2. Burwell R
    3. Burchinal M

    (1993) Severity of spatial learning impairment in aging: development of a learning index for performance in the morris water maze

    Behavioral Neuroscience 107:618–626.

    https://doi.org/10.1037/0735-7044.107.4.618

    • PubMed
    • Google Scholar
23. 1. Gallagher M
    2. Nicolle MM

    (1993) Animal models of normal aging: relationship between cognitive decline and markers in hippocampal circuitry

    Behavioural Brain Research 57:155–162.

    https://doi.org/10.1016/0166-4328(93)90131-9

    • PubMed
    • Google Scholar
24. 1. Gallagher M
    2. Pelleymounter MA

    (1988) Spatial learning deficits in old rats: a model for memory decline in the aged

    Neurobiology of Aging 9:549–556.

    https://doi.org/10.1016/S0197-4580(88)80112-X

    • PubMed
    • Google Scholar
25. 1. Gant JC
    2. Sama MM
    3. Landfield PW
    4. Thibault O

    (2006) Early and simultaneous emergence of multiple hippocampal biomarkers of aging is mediated by Ca2+-induced Ca2+ release

    Journal of Neuroscience 26:3482–3490.

    https://doi.org/10.1523/JNEUROSCI.4171-05.2006

    • PubMed
    • Google Scholar
26. 1. Gruart A
    2. Benito E
    3. Delgado-García JM
    4. Barco A

    (2012) Enhanced cAMP response element-binding protein activity increases neuronal excitability, hippocampal long-term potentiation, and classical eyeblink conditioning in alert behaving mice

    Journal of Neuroscience 32:17431–17441.

    https://doi.org/10.1523/JNEUROSCI.4339-12.2012

    • PubMed
    • Google Scholar
27. 1. Han JH
    2. Kushner SA
    3. Yiu AP
    4. Cole CJ
    5. Matynia A
    6. Brown RA
    7. Neve RL
    8. Guzowski JF
    9. Silva AJ
    10. Josselyn SA

    (2007) Neuronal competition and selection during memory formation

    Science 316:457–460.

    https://doi.org/10.1126/science.1139438

    • PubMed
    • Google Scholar
28. 1. Han MH
    2. Bolaños CA
    3. Green TA
    4. Olson VG
    5. Neve RL
    6. Liu RJ
    7. Aghajanian GK
    8. Nestler EJ

    (2006) Role of cAMP response element-binding protein in the rat locus ceruleus: regulation of neuronal activity and opiate withdrawal behaviors

    Journal of Neuroscience 26:4624–4629.

    https://doi.org/10.1523/JNEUROSCI.4701-05.2006

    • PubMed
    • Google Scholar
29. 1. Hu YS
    2. Long N
    3. Pigino G
    4. Brady ST
    5. Lazarov O

    (2013) Molecular mechanisms of environmental enrichment: impairments in akt/GSK3β, neurotrophin-3 and CREB signaling

    PLoS One 8:e64460.

    https://doi.org/10.1371/journal.pone.0064460

    • PubMed
    • Google Scholar
30. 1. Josselyn SA
    2. Shi C
    3. Carlezon WA
    4. Neve RL
    5. Nestler EJ
    6. Davis M

    (2001)

    Long-term memory is facilitated by cAMP response element-binding protein overexpression in the amygdala

    Journal of Neuroscience 21:2404–2412.

    • PubMed
    • Google Scholar
31. 1. Kaang BK
    2. Kandel ER
    3. Grant SG

    (1993) Activation of cAMP-responsive genes by stimuli that produce long-term facilitation in aplysia sensory neurons

    Neuron 10:427–435.

    https://doi.org/10.1016/0896-6273(93)90331-K

    • PubMed
    • Google Scholar
32. 1. Karege F
    2. Schwald M
    3. Lambercy C
    4. Murama JJ
    5. Cisse M
    6. Malafosse A

    (2001) A non-radioactive assay for the cAMP-dependent protein kinase activity in rat brain homogenates and age-related changes in hippocampus and cortex

    Brain Research 903:86–93.

    https://doi.org/10.1016/S0006-8993(01)02409-X

    • PubMed
    • Google Scholar
33. 1. Kida S
    2. Josselyn SA
    3. Peña de Ortiz S
    4. Kogan JH
    5. Chevere I
    6. Masushige S
    7. Silva AJ

    (2002) CREB required for the stability of new and reactivated fear memories

    Nature Neuroscience 5:348–355.

    https://doi.org/10.1038/nn819

    • PubMed
    • Google Scholar
34. 1. Knuttinen MG
    2. Gamelli AE
    3. Weiss C
    4. Power JM
    5. Disterhoft JF

    (2001a) Age-related effects on eyeblink conditioning in the F344 X BN F1 hybrid rat

    Neurobiology of Aging 22:1–8.

    https://doi.org/10.1016/S0197-4580(00)00194-9

    • PubMed
    • Google Scholar
35. 1. Knuttinen MG
    2. Power JM
    3. Preston AR
    4. Disterhoft JF

    (2001b) Awareness in classical differential eyeblink conditioning in young and aging humans

    Behavioral Neuroscience 115:747–757.

    https://doi.org/10.1037/0735-7044.115.4.747

    • PubMed
    • Google Scholar
36. 1. Kronforst-Collins MA
    2. Moriearty PL
    3. Ralph M
    4. Becker RE
    5. Schmidt B
    6. Thompson LT
    7. Disterhoft JF

    (1997) Metrifonate treatment enhances acquisition of eyeblink conditioning in aging rabbits

    Pharmacology Biochemistry and Behavior 56:103–110.

    https://doi.org/10.1016/S0091-3057(96)00164-5

    • Google Scholar
37. 1. Kumar A
    2. Foster T

    (2007) Environmental enrichment decreases the afterhyperpolarization in senescent rats

    Brain Research 1130:103–107.

    https://doi.org/10.1016/j.brainres.2006.10.037

    • PubMed
    • Google Scholar
38. 1. Landfield PW
    2. Pitler TA

    (1984) Prolonged Ca²+-dependent afterhyperpolarizations in hippocampal neurons of aged rats

    Science 226:1089–1092.

    https://doi.org/10.1126/science.6494926

    • PubMed
    • Google Scholar
39. 1. Lopez de Armentia M
    2. Jancic D
    3. Olivares R
    4. Alarcon JM
    5. Kandel ER
    6. Barco A

    (2007) cAMP response element-binding protein-mediated gene expression increases the intrinsic excitability of CA1 pyramidal neurons

    Journal of Neuroscience 27:13909–13918.

    https://doi.org/10.1523/JNEUROSCI.3850-07.2007

    • PubMed
    • Google Scholar
40. 1. Matthews EA
    2. Linardakis JM
    3. Disterhoft JF

    (2009) The fast and slow afterhyperpolarizations are differentially modulated in hippocampal neurons by aging and learning

    Journal of Neuroscience 29:4750–4755.

    https://doi.org/10.1523/JNEUROSCI.0384-09.2009

    • PubMed
    • Google Scholar
41. 1. Monti B
    2. Berteotti C
    3. Contestabile A

    (2005) Dysregulation of memory-related proteins in the hippocampus of aged rats and their relation with cognitive impairment

    Hippocampus 15:1041–1049.

    https://doi.org/10.1002/hipo.20099

    • PubMed
    • Google Scholar
42. 1. Mouravlev A
    2. Dunning J
    3. Young D
    4. During MJ

    (2006) Somatic gene transfer of cAMP response element-binding protein attenuates memory impairment in aging rats

    PNAS 103:4705–4710.

    https://doi.org/10.1073/pnas.0506137103

    • PubMed
    • Google Scholar
43. 1. Moyer JR
    2. Power JM
    3. Thompson LT
    4. Disterhoft JF

    (2000)

    Increased excitability of aged rabbit CA1 neurons after trace eyeblink conditioning

    Journal of Neuroscience 20:5476–5482.

    • PubMed
    • Google Scholar
44. 1. Moyer JR
    2. Thompson LT
    3. Black JP
    4. Disterhoft JF

    (1992)

    Nimodipine increases excitability of rabbit CA1 pyramidal neurons in an age- and concentration-dependent manner

    Journal of Neurophysiology 68:2100–2109.

    • PubMed
    • Google Scholar
45. 1. Moyer JR
    2. Thompson LT
    3. Disterhoft JF

    (1996)

    Trace eyeblink conditioning increases CA1 excitability in a transient and learning-specific manner

    Journal of Neuroscience 16:5536–5546.

    • PubMed
    • Google Scholar
46. 1. Neve RL
    2. Neve KA
    3. Nestler EJ
    4. Carlezon WA

    (2005) Use of herpes virus amplicon vectors to study brain disorders

    BioTechniques 39:381–391.

    https://doi.org/10.2144/05393PS01

    • PubMed
    • Google Scholar
47. 1. Núñez-Santana FL
    2. Oh MM
    3. Antion MD
    4. Lee A
    5. Hell JW
    6. Disterhoft JF

    (2014) Surface L-type Ca2+ channel expression levels are increased in aged hippocampus

    Aging Cell 13:111–120.

    https://doi.org/10.1111/acel.12157

    • PubMed
    • Google Scholar
48. 1. Oh MM
    2. Disterhoft JF

    (2015) Increased Excitability of Both Principal Neurons and Interneurons during Associative Learning

    The Neuroscientist 21:372–384.

    https://doi.org/10.1177/1073858414537382

    • PubMed
    • Google Scholar
49. 1. Oh MM
    2. McKay BM
    3. Power JM
    4. Disterhoft JF

    (2009) Learning-related postburst afterhyperpolarization reduction in CA1 pyramidal neurons is mediated by protein kinase A

    PNAS 106:1620–1625.

    https://doi.org/10.1073/pnas.0807708106

    • PubMed
    • Google Scholar
50. 1. Oh MM
    2. Oliveira FA
    3. Waters J
    4. Disterhoft JF

    (2013) Altered calcium metabolism in aging CA1 hippocampal pyramidal neurons

    Journal of Neuroscience  33:7905–7911.

    https://doi.org/10.1523/JNEUROSCI.5457-12.2013

    • PubMed
    • Google Scholar
51. 1. Oh MM
    2. Power JM
    3. Thompson LT
    4. Moriearty PL
    5. Disterhoft JF

    (1999)

    Metrifonate increases neuronal excitability in CA1 pyramidal neurons from both young and aging rabbit hippocampus

    Journal of Neuroscience 19:1814–1823.

    • PubMed
    • Google Scholar
52. 1. Pittenger C
    2. Huang YY
    3. Paletzki RF
    4. Bourtchouladze R
    5. Scanlin H
    6. Vronskaya S
    7. Kandel ER

    (2002) Reversible inhibition of CREB/ATF transcription factors in region CA1 of the dorsal hippocampus disrupts hippocampus-dependent spatial memory

    Neuron 34:447–462.

    https://doi.org/10.1016/S0896-6273(02)00684-0

    • PubMed
    • Google Scholar
53. 1. Pugazhenthi S
    2. Wang M
    3. Pham S
    4. Sze CI
    5. Eckman CB

    (2011) Downregulation of CREB expression in Alzheimer's brain and in Aβ-treated rat hippocampal neurons

    Molecular Neurodegeneration 6:60.

    https://doi.org/10.1186/1750-1326-6-60

    • PubMed
    • Google Scholar
54. 1. Restivo L
    2. Tafi E
    3. Ammassari-Teule M
    4. Marie H

    (2009) Viral-mediated expression of a constitutively active form of CREB in hippocampal neurons increases memory

    Hippocampus 19:228–234.

    https://doi.org/10.1002/hipo.20527

    • PubMed
    • Google Scholar
55. 1. Rogalski EJ
    2. Gefen T
    3. Shi J
    4. Samimi M
    5. Bigio E
    6. Weintraub S
    7. Geula C
    8. Mesulam MM

    (2013) Youthful memory capacity in old brains: anatomic and genetic clues from the northwestern SuperAging project

    Journal of Cognitive Neuroscience 25:29–36.

    https://doi.org/10.1162/jocn_a_00300

    • PubMed
    • Google Scholar
56. 1. Satoh J
    2. Tabunoki H
    3. Arima K

    (2009) Molecular network analysis suggests aberrant CREB-mediated gene regulation in the alzheimer disease hippocampus

    Disease Markers 27:239–252.

    https://doi.org/10.1155/2009/618619

    • PubMed
    • Google Scholar
57. 1. Sekeres MJ
    2. Neve RL
    3. Frankland PW
    4. Josselyn SA

    (2010) Dorsal hippocampal CREB is both necessary and sufficient for spatial memory

    Learning & Memory 17:280–283.

    https://doi.org/10.1101/lm.1785510

    • PubMed
    • Google Scholar
58. 1. Suzuki A
    2. Fukushima H
    3. Mukawa T
    4. Toyoda H
    5. Wu LJ
    6. Zhao MG
    7. Xu H
    8. Shang Y
    9. Endoh K
    10. Iwamoto T
    11. Mamiya N
    12. Okano E
    13. Hasegawa S
    14. Mercaldo V
    15. Zhang Y
    16. Maeda R
    17. Ohta M
    18. Josselyn SA
    19. Zhuo M
    20. Kida S

    (2011) Upregulation of CREB-mediated transcription enhances both short- and long-term memory

    Journal of Neuroscience 31:8786–8802.

    https://doi.org/10.1523/JNEUROSCI.3257-10.2011

    • PubMed
    • Google Scholar
59. 1. Thompson LT
    2. Moyer JR
    3. Disterhoft JF

    (1996) Trace eyeblink conditioning in rabbits demonstrates heterogeneity of learning ability both between and within age groups

    Neurobiology of Aging 17:619–629.

    https://doi.org/10.1016/0197-4580(96)00026-7

    • PubMed
    • Google Scholar
60. 1. Tombaugh GC
    2. Rowe WB
    3. Rose GM

    (2005) The slow afterhyperpolarization in hippocampal CA1 neurons covaries with spatial learning ability in aged Fisher 344 rats

    Journal of Neuroscience 25:2609–2616.

    https://doi.org/10.1523/JNEUROSCI.5023-04.2005

    • PubMed
    • Google Scholar
61. 1. Viosca J
    2. Lopez de Armentia M
    3. Jancic D
    4. Barco A

    (2009a) Enhanced CREB-dependent gene expression increases the excitability of neurons in the basal amygdala and primes the consolidation of contextual and cued fear memory

    Learning & Memory 16:193–197.

    https://doi.org/10.1101/lm.1254209

    • PubMed
    • Google Scholar
62. 1. Viosca J
    2. Malleret G
    3. Bourtchouladze R
    4. Benito E
    5. Vronskava S
    6. Kandel ER
    7. Barco A

    (2009b) Chronic enhancement of CREB activity in the hippocampus interferes with the retrieval of spatial information

    Learning & Memory 16:198–209.

    https://doi.org/10.1101/lm.1220309

    • PubMed
    • Google Scholar
63. 1. Weible AP
    2. Oh MM
    3. Lee G
    4. Disterhoft JF

    (2004) Galantamine facilitates acquisition of hippocampus-dependent trace eyeblink conditioning in aged rabbits

    Learning & Memory 11:108–115.

    https://doi.org/10.1101/lm.69804

    • PubMed
    • Google Scholar
64. 1. Yin Y
    2. Gao D
    3. Wang Y
    4. Wang Z-H
    5. Wang X
    6. Ye J
    7. Wu D
    8. Fang L
    9. Pi G
    10. Yang Y
    11. Wang X-C
    12. Lu C
    13. Ye K
    14. Wang J-Z

    (2016) Tau accumulation induces synaptic impairment and memory deficit by calcineurin-mediated inactivation of nuclear CaMKIV/CREB signaling

    PNAS 113:E3773–E3781.

    https://doi.org/10.1073/pnas.1604519113

    • Google Scholar
65. 1. Yiu AP
    2. Mercaldo V
    3. Yan C
    4. Richards B
    5. Rashid AJ
    6. Hsiang HL
    7. Pressey J
    8. Mahadevan V
    9. Tran MM
    10. Kushner SA
    11. Woodin MA
    12. Frankland PW
    13. Josselyn SA

    (2014) Neurons are recruited to a memory trace based on relative neuronal excitability immediately before training

    Neuron 83:722–735.

    https://doi.org/10.1016/j.neuron.2014.07.017

    • PubMed
    • Google Scholar
66. 1. Yiu AP
    2. Rashid AJ
    3. Josselyn SA

    (2011) Increasing CREB function in the CA1 region of dorsal hippocampus rescues the spatial memory deficits in a mouse model of alzheimer's disease

    Neuropsychopharmacology 36:2169–2186.

    https://doi.org/10.1038/npp.2011.107

    • PubMed
    • Google Scholar
67. 1. Yu XW
    2. Oh MM
    3. Disterhoft JF

    (2016) CREB, cellular excitability, and cognition: Implications for aging

    Behavioural Brain Research.

    https://doi.org/10.1016/j.bbr.2016.07.042

    • PubMed
    • Google Scholar
68. 1. Zhang L
    2. Ouyang M
    3. Ganellin CR
    4. Thomas SA

    (2013) The slow afterhyperpolarization: a target of β1-adrenergic signaling in hippocampus-dependent memory retrieval

    Journal of Neuroscience 33:5006–5016.

    https://doi.org/10.1523/JNEUROSCI.3834-12.2013

    • PubMed
    • Google Scholar
69. 1. Zhou Y
    2. Won J
    3. Karlsson MG
    4. Zhou M
    5. Rogerson T
    6. Balaji J
    7. Neve R
    8. Poirazi P
    9. Silva AJ

    (2009) CREB regulates excitability and the allocation of memory to subsets of neurons in the amygdala

    Nature Neuroscience 12:1438–1443.

    https://doi.org/10.1038/nn.2405

    • PubMed
    • Google Scholar

Author details

1. Xiao-Wen Yu

   Department of Physiology, Northwestern University,Feinberg School of Medicine, Chicago, United States

   Contribution

   X-WY, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

   "This ORCID iD identifies the author of this article:" 0000-0002-8974-0085

2. Daniel M Curlik II

   1. Department of Physiology, Northwestern University,Feinberg School of Medicine, Chicago, United States
   2. Department of Behavioral Sciences, Psychology Program, York College of Pennsylvania, York, United States

   Contribution

   DMC, Conception and design, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

3. M Matthew Oh

   Department of Physiology, Northwestern University,Feinberg School of Medicine, Chicago, United States

   Contribution

   MMO, Conception and design, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

   "This ORCID iD identifies the author of this article:" 0000-0002-6702-5785

4. Jerry CP Yin

   Departments of Genetics and Neurology, University of Wisconsin-Madison, Madison, United States

   Contribution

   JCPY, Conception and design, Analysis and interpretation of data, Drafting or revising the article, Contributed unpublished essential data or reagents

   Competing interests

   The authors declare that no competing interests exist.

5. John F Disterhoft

   Department of Physiology, Northwestern University,Feinberg School of Medicine, Chicago, United States

   Contribution

   JFD, Conception and design, Analysis and interpretation of data, Drafting or revising the article

   For correspondence

   jdisterhoft@northwestern.edu

   Competing interests

   The authors declare that no competing interests exist.

   "This ORCID iD identifies the author of this article:" 0000-0002-8817-7913

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