Memory loss in older people is a serious and widespread problem that affects up to 50% of those over the age of 85. It is a key symptom of dementia, but despite the growing impact of this disease on society, there are no treatments currently available that can effectively stop or delay the progression of the symptoms.

One therapy that may reduce memory loss is called deep brain stimulation. Electrodes are implanted into the brain and used to stimulate brain cells in particular areas of the brain to alter mental and emotional processes. Deep brain stimulation is already used to treat Parkinson's disease, depression and other conditions that affect how the brain works.

Liu et al. studied the effect of deep brain stimulation on memory in rats. The experiments show that middle-aged rats performed less well in short- and long-term memory tests than young rats. Next, Liu et al. investigated whether deep brain stimulation could improve memory in the middle-aged rats. The electrodes were positioned to stimulate a region near the front of the brain called the ‘ventromedial prefrontal cortex’; this region is important for the formation and recall of memories. Liu et al. then gave the rats a series of memory tasks that tested their recall after 90 minutes (to test their short-term memory), and after 24 hours (to test long-term memory).

The experiments reveal that a brief stimulation of brain cells in this region of the brain improved the rats' short-term memory, but not their long-term memory. However, more sustained stimulation of this region of the brain improved both the short-term and long-term memory of the rats. Furthermore, deep brain stimulation led to the formation of new brain cells in another region of the brain called the hippocampus, which is also involved in memory. The hippocampus had not been in direct contact with the electrodes so the increase in brain cells was due to its connections with the stimulated ventromedial prefrontal cortex.

Liu et al.'s findings suggest that deep brain stimulation of the ventromedial prefrontal cortex has the potential to be developed into a therapy to treat dementia and other conditions that lead to memory loss in humans.

Memory loss is the key symptom of dementia-related disorders along with impaired cognitive functioning such as language or reasoning. It is usually caused by Alzheimer's disease and other age-related dementia. Its prevalence doubles from a low rate in 60–64 age group to 40–50% of those older than 85 (Lobo et al., 2000). Dementia is a progressive disease, which has a detrimental impact on the quality of life for patients. To date, pharmacological treatments for dementia have limited effects and there are no known treatments that cure or delay the progression of this memory impairment (Doody et al., 2014; Salloway et al., 2014). Therefore, a novel non-pharmacological approach such as deep brain stimulation (DBS) is currently considered as an alternative treatment to reduce the symptomatic and progression of this memory deterioration (Hescham et al., 2013a).

DBS, a technique of minimally invasive surgical implantation of electrodes with delivering of electrical impulses into the brain, has been demonstrated to control a wide range of neurological disorders and neuropsychiatric diseases (Sesia et al., 2009; Temel et al., 2012b; Temel and Lim, 2013). In line with these developments, evidence from recent studies suggests that DBS might enhance memory functions when particular brain areas are stimulated (Hamani et al., 2008; Laxton et al., 2010; Suthana et al., 2012; Hescham et al., 2013b). Of particular interest, DBS of the subgenual anterior cingulate cortex or the ventromedial prefrontal cortex (vmPFC) induced striking antidepressant activity in both patients and animal studies (Mayberg et al., 2005; Lozano et al., 2008; Hamani et al., 2010b; Kennedy et al., 2011; Temel and Lim, 2013; Lim et al., 2015b). Despite encouraging results, no studies have shown the putative role of vmPFC DBS in learning and memory performance. In the realm of cognitive function, there is empirical evidence indicating that vmPFC plays an important role in the formation, consolidation, and retrieval of memory, as well as reward and decision making (Maviel et al., 2004; Euston et al., 2012). Based on the human imaging and rodent studies, the vmPFC was significantly activated during the recall of remote memory (Bontempi et al., 1999; Takashima et al., 2006a, 2006b; Gais et al., 2007), while its inactivation caused memory impairment when tested in the radial arm-maze (Maviel et al., 2004), the Morris water-maze (MWM) (Teixeira et al., 2006), and the contextual fear conditioning (Frankland et al., 2004). In line with these studies, malfunctioning has also been reported in the hippocampus and the vmPFC (which received robust projections from the hippocampal formation) in early stages of Alzheimer's disease, frontotemporal dementia, and healthy aging-related memory impairments (Salat et al., 2001; Lindberg et al., 2012).

Given the potential mechanisms involved by DBS including the increase of hippocampal brain-derived neurotrophic factor (BDNF) levels (Hamani et al., 2012; Ying et al., 2012) and neurogenesis-related functions (Toda et al., 2008; Kadar et al., 2011; Stone et al., 2011), we tested the hypothesis that vmPFC DBS-enhanced memory function by modulating the hippocampal neurogenic activity in the middle-aged rat model with aging-related memory impairment. The use of this animal model was supported by previous data that showed aged-related deficits in both the memory and the hippocampal functioning (Rex et al., 2005; Kaczorowski and Disterhoft, 2009). In acute DBS, animals were tested with either high- or low-frequency stimulation (HFS or LFS) at various amplitudes using the conventional novel-object recognition (NOR) test. Subsequently, another set of animals was used to assess the chronic stimulation effects on memory enhancement using the NOR and the MWM tests. For investigation of the underlying mechanism, we analyzed the effects of chronic stimulation on the molecular and cellular levels of hippocampal neurogenesis-related functions.

The present findings confirm the results of previous studies of progressive age-related memory impairment in the middle-aged rats (Rex et al., 2005; Kaczorowski and Disterhoft, 2009). We next conducted electrical stimulation in this animal model of memory deficit, using HFS and LFS with various stimulation current intensities in the NOR test. Our results showed that HFS at 200 μA and LFS at 50, 200, and 400 μA significantly enhanced the memory functions in the short-, but not the long-term memory retention interval when compared to the sham. We next carried out chronic stimulation in this middle-aged rat model. We hypothesized that chronic stimulation would increase both the short- and long-term memory functions via a mechanism of enhanced hippocampal neuroplasticity. Previous studies have shown that memory deficits were partly due to the disruption of the hippocampal neuroplasticity (Deupree et al., 1993; Rex et al., 2005). Therefore, our hypothesis was driven by findings that DBS in various brain targets increased BDNF level (Hamani et al., 2012; Ying et al., 2012) and enhanced neurogenesis-related functions (Toda et al., 2008; Kadar et al., 2011; Stone et al., 2011) in the hippocampus. Further, this hypothesis was also supported by the fact that the increased BDNF level and neurogenesis function in the hippocampus were strongly correlated with the hippocampal-dependent memory tests (Drapeau et al., 2003; Erickson et al., 2011). Thus, after chronic stimulation, we found significant improvement in both the short- and long-term memories in the NOR test, as well as the spatial memory performances during the MWM task as compared to the sham.

In the acute stimulation experiment, we found that the behavioral effects of vmPFC stimulation were dependent on the stimulation frequency and current intensity. Although these findings are consistent with previous reports (Hamani et al., 2010a; Hescham et al., 2013b), the mechanisms of the stimulation parameter dependency in regulation of memory functions remain largely obscure. Nonetheless, it is postulated that the neurons in the vmPFC are highly sensitive to specific stimulation settings for induction of either long-term potentiation (LTP) or depression (LTD). This notion was highly supported by the findings in which the vmPFC synapses are potentially vulnerable to LTP or LTD strengthening after specific type of stimulation (Herry and Garcia, 2002). It has been found that the prefrontal cortex neurons could undergo LTP with rapid and stable potentiation in the prelimbic synapses after high-frequency tetanic stimulation of the hippocampal CA1/subicular region (Laroche et al., 1990). Such a LTP-like plasticity in the vmPFC after hippocampal HFS has been shown to be dependent on α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) and N-methyl-D-aspartate (NMDA)-receptor, which indicates a crucial role for the synaptic potentiation in the hippocampal-vmPFC pathway in rapid memory consolidation (Laroche et al., 2000). Although HFS and LFS at specific amplitudes were effective for memory enhancement, it is noteworthy that LFS induced negative effects on the anxiety-related behaviors (Lim et al., 2015b). Furthermore, HFS of the vmPFC has been shown to reduce conditioned fear and enhance the extinction of aversive memory (Milad and Quirk, 2002; Milad et al., 2004), in contrast to LFS, which induced impairment in extinction of conditioned fear (Shehadi and Maroun, 2012). Since previous studies of vmPFC HFS produced robust antidepressant-like behaviors (Lim et al., 2015a, 2015b), we therefore applied this stimulation parameter in the chronic stimulation experiment to test the hypothesis that it would restore the memory deficits for both the short- and long-term memory functions of the middle-aged rats.

As might be expected for the effects after chronic stimulation, there was an improvement on memory function in the short- but not the long-term memory retention interval when the animals were tested with no-HFS prior to the NOR task. Strikingly, we found a remarkable reversal of memory deficits in both the short- and long-term memory of the animals that received HFS prior to the NOR test as compared to the non-stimulated sham. Congruently, chronic vmPFC HFS significantly improved the spatial navigation performances when conducted in a hippocampal-dependent memory MWM test. In the present data, we clearly distinguished a role for the vmPFC in regulation of both the short- and long-term memory functions. In most studies, short-term memory is generally regarded as memory spanning from seconds to several minutes or hours, while long-term memory is usually last from hours to several days or longer (Nagai et al., 2007; Euston et al., 2012). Albeit many studies have indicated that vmPFC is involved in the expression of long-term memory (Maviel et al., 2004; Teixeira et al., 2006), there are also findings supporting that vmPFC is involved in consolidation and retrieval of recently acquired memories (Blum et al., 2006; Leon et al., 2010). Thus, it is likely that the vmPFC HFS potentiated the initial hippocampal encoding during the acquisition phase, which was then followed by enhanced retrieval during the short- and long-term memory recalls. Taken together, these findings further implicate a specific role for the vmPFC HFS in facilitation of rapid consolidation and retrieval of the short- and long-term memory processes in the hippocampus.

HFS of the vmPFC has not only been demonstrated for memory enhancement in the middle-aged memory deficit rat model, but also induced profound antidepressant-like behaviors in the experimental animal studies (Lim et al., 2015a; 2015b). Interestingly, the effects of memory improvement by vmPFC HFS, as characterized by the increased novelty seeking in the NOR and MWM tasks, were highly associated with the stimulation effects on reduction in anxiety behavior. These results confirm previous findings that animals with lower anxiety or fear level displayed higher novelty seeking behavior, particularly in the elevated plus-maze and light–dark box tests (Kabbaj et al., 2000; Stead et al., 2006). In consistent with the data found in the animal model of depression, rats undergoing chronic stress exhibited anxious and low exploratory behaviors (Lim et al., 2015b), as well as impairment in spatial memory task performances (Conrad et al., 1996; Beck and Luine, 1999). Apparently, chronic stress produces pathological alterations on the molecular and morphological levels in the hippocampus that is involved in the regulation of both the spatial memory formation and emotional behaviors. Thus, our experiments found that the memory enhancement effect is likely to be accompanied by the vmPFC DBS-induced anxiolytic effects via the mechanisms of neurogenesis and dendritic remodeling in the hippocampal neurons.

Given the prominent anatomical connectivity between the hippocampus and vmPFC (Jay and Witter, 1991; Cenquizca and Swanson, 2007), it was observed that vmPFC HFS drove the local neural activity as characterized by c-Fos-ir activation in the subiculum, DG, as well as a marginal increase in the CA1 field of the hippocampus. Although there is no direct connection from vmPFC to the hippocampus, it is possible that the effects of vmPFC HFS on the hippocampal neural activity are mediated by a reciprocal bisynaptic pathway through the nucleus reunions or the lateral entorhinal cortex (Burwell and Amaral, 1998; Vertes et al., 2007). Besides, the neural activity in the hippocampus could probably be activated by either antidromic or orthodromic stimulation that possibly achieved by a current spread from the vmPFC structure to the neighboring axon bundles—the minor forceps of the corpus callosum (Lim et al., 2015b). As a result, the hippocampal regions would eventually be activated for an induction of LTP to strengthen its synaptic plasticity for memory processes. Of particular interest, a tractography analysis by diffusion tensor imaging provides evidence for this structural connectivity that HFS of the subgenual cingulate gyrus (generally considered to be homologue of the rat vmPFC), showed connections to the medial frontal cortex, anterior and posterior cingulate, and the anterior medial temporal lobe (i.e., amygdala-hippocampus) (Gutman et al., 2009). The connections of the hippocampus and amygdala to the vmPFC have been previously investigated by anatomical and electrophysiological studies (Laroche et al., 1990; Jay and Witter, 1991). It has been shown that the excitatory and inhibitory inputs from the amygdala and hippocampus were converged and interact in the vmPFC (Ishikawa and Nakamura, 2003), implying that activation of the amygdalar-hippocampal neurons might be crucial for vmPFC neurons in memory regulation. More importantly, the electrophysiological studies have provided concrete evidence of functional interaction between the vmPFC and hippocampus in which their theta oscillations were highly synchronized as measured by both the spike-theta phase locking and local field potential coherence, during memory acquisition and retrieval in spatial tasks (Jones and Wilson, 2005; Siapas et al., 2005; Benchenane et al., 2010). Based on this evidence, we suggested that the rapid encoding and retrieval of memory depend largely on the bidirectional regulation of synaptic connectivity between the vmPFC and hippocampus; while the disruption of its connection affect the learning and memory functions, which are commonly identified in patients suffering from dementia (Salat et al., 2001).

In line with our findings, HFS of the anterior nucleus of the thalamus and the entorhinal cortex has been demonstrated to increase neurogenesis (Toda et al., 2008) and memory functions, particularly spatial memory measured in the MWM (Stone et al., 2011) and enhanced performance on a delayed non-matching to sample task (Hamani et al., 2011). In this study, we found that vmPFC HFS induced upregulation of neurogenesis-associated genes with increased neural progenitors cells and dendritic spines in the DG of the hippocampus. In agreement with our previous microarray data (Kadar et al., 2011), chronic HFS has been shown to modulate the hippocampal genes that involved in the proliferation and neurogenesis-related functions, as well as genes supporting for neural differentiation, migration and maturation. Although we observed no differences for the Timp1 (neuroprotection), Ccl2 (neural differentiation), and BDNF (synaptic plasticity) gene expression, there was an overall increase in their fold-change with approximately 1.2–2 fold after chronic vmPFC HFS. Notably, we found a strong induction of upregulation in the Angpt2 gene (4.8-fold) that promotes neuronal differentiation, migration and neuroprotection (Liu et al., 2009), as well as NeuN/Rbfox3 gene (2-fold), which plays an essential role for neural progenitor cells differentiation and maturation (Kim et al., 2009, 2013). Further, our present observations were also supported by earlier works demonstrating that vmPFC HFS induced significant increase of BDNF and serotonin (5-HT) levels in the hippocampus (Hamani et al., 2012). Recent studies have shown that the increase of 5-HT and BDNF expression in the hippocampus regulate synaptic plasticity, as well as cognitive and mood-related behaviors. It is well-known that both the 5-HT and BDNF promote neurogenesis by enhancing the synaptogenesis, neuronal differentiation, and survival particularly for memory acquisition and consolidation (Gaspar et al., 2003; Lu and Chang, 2004; Pang et al., 2004). Although no microdialysis data were provided with regard to the extracellular levels of 5-HT and BDNF after chronic vmPFC HFS, the increased neurogenesis effects as obtained from this study clearly indicate that its plausible mechanism is facilitated by the release of 5-HT and enhanced BDNF levels (Hamani et al., 2012). Importantly, the vmPFC HFS effects on the behavioral observation of improved memory functions and the neurogenesis have indicated that a strong synaptic network circuitry has been established within the DG for integration of new information and memory storage. In support of this notion, previous studies have demonstrated that the increased neurogenesis was highly associated with enhanced learning and memory, while its decrease caused memory impairment (van Praag et al., 1999; Shors et al., 2001). Although the present study has identified the DBS-induced memory enhancement by neurogenesis, there is a possibility that these effects are mediated by other non-neurogenic mechanisms such as modulation of the neurotransmission (via acetylcholine, dopamine, 5-HT, etc), synaptic potentiation by the AMPA/NMDA receptor trafficking, and enhancement of the BDNF or CREB (cAMP response element-binding protein) function (Hamani et al., 2012; Stern and Alberni, 2012).

The above findings prompted us to further examine whether the increase of neurogenesis-related functions is associated with the effects of memory enhancement by vmPFC HFS. Our correlation analysis of gene expression revealed that the Syn was strongly associated with the Nes and Dcx genes, suggesting that vmPFC HFS might possibly cause an alteration of increased dendritic synaptogenesis, particularly in the hippocampal DG where transcriptional process for Nes and Dcx genes occurs. Consistent with this interpretation, we have demonstrated the increase of dendritic spines in the Golgi-impregnated cells of the hippocampal DG. This observation was supported by a previous study which showed that electrical stimulation affected the axonal path in cultured Xenopus neurons that was mediated by elevation of both cytoplasmic Ca²⁺ and cyclic adenosine monophosphate levels (Ming et al., 2001). Importantly, our behavioral correlates show that the spatial memory performances were associated with the cell proliferation in the DG, indicating that neurogenesis in the DG is vital for the hippocampal-dependent learning and memory processes.

In conclusion, our findings suggest that chronic vmPFC HFS induces long-lasting effects on memory performances and its underlying mechanism is possibly mediated by an enhanced neurogenesis in the hippocampus. Despite the fact that this structure has been previously shown for antidepressant-like activities, it might as well serve as a new effective DBS target for aged-related memory deficits. Thus, this translational research provides an additional window for a possibility of future clinical trials on this potential brain target for memory enhancement.

1. 1. Beck KD
   2. Luine VN

   (1999) Food deprivation modulates chronic stress effects on object recognition in male rats: role of monoamines and amino acids

   Brain Research 830:56–71.

   https://doi.org/10.1016/S0006-8993(99)01380-3

   • Google Scholar
2. 1. Benchenane K
   2. Peyrache A
   3. Khamassi M
   4. Tierney PL
   5. Gioanni Y
   6. Battaglia FP
   7. Wiener SI

   (2010) Coherent theta oscillations and reorganization of spike timing in the hippocampal- prefrontal network upon learning

   Neuron 66:921–936.

   https://doi.org/10.1016/j.neuron.2010.05.013

   • Google Scholar
3. 1. Blum S
   2. Hebert AE
   3. Dash PK

   (2006) A role for the prefrontal cortex in recall of recent and remote memories

   Neuroreport 17:341–344.

   https://doi.org/10.1097/01.wnr.0000201509.53750.bc

   • Google Scholar
4. 1. Bontempi B
   2. Laurent-Demir C
   3. Destrade C
   4. Jaffard R

   (1999) Time-dependent reorganization of brain circuitry underlying long-term memory storage

   Nature 400:671–675.

   https://doi.org/10.1038/23270

   • Google Scholar
5. 1. Burwell RD
   2. Amaral DG

   (1998) Cortical afferents of the perirhinal, postrhinal, and entorhinal cortices of the rat

   The Journal of Comparative Neurology 398:179–205.

   https://doi.org/10.1002/(SICI)1096-9861(19980824)398:23.0.CO;2-Y

   • Google Scholar
6. 1. Cenquizca LA
   2. Swanson LW

   (2007) Spatial organization of direct hippocampal field CA1 axonal projections to the rest of the cerebral cortex

   Brain Research Reviews 56:1–26.

   https://doi.org/10.1016/j.brainresrev.2007.05.002

   • Google Scholar
7. 1. Conrad CD
   2. Galea LA
   3. Kuroda Y
   4. McEwen BS

   (1996) Chronic stress impairs rat spatial memory on the Y maze, and this effect is blocked by tianeptine pretreatment

   Behavioral Neuroscience 110:1321–1334.

   https://doi.org/10.1037/0735-7044.110.6.1321

   • Google Scholar
8. 1. Davis HP
   2. Small SA
   3. Stern Y
   4. Mayeux R
   5. Feldstein SN
   6. Keller FR

   (2003) Acquisition, recall, and forgetting of verbal information in long-term memory by young, middle-aged, and elderly individuals

   Cortex 39:1063–1091.

   https://doi.org/10.1016/S0010-9452(08)70878-5

   • Google Scholar
9. 1. Deupree DL
   2. Bradley J
   3. Turner DA

   (1993) Age-related alterations in potentiation in the CA1 region in F344 rats

   Neurobiology of Aging 14:249–258.

   https://doi.org/10.1016/0197-4580(93)90009-Z

   • Google Scholar
10. 1. Doody RS
    2. Thomas RG
    3. Farlow M
    4. Iwatsubo T
    5. Vellas B
    6. Joffe S
    7. Kieburtz K
    8. Raman R
    9. Sun X
    10. Aisen PS
    11. Siemers E
    12. Liu-Seifert H
    13. Mohs R
    14. Alzheimer's Disease Cooperative Study Steering Committee
    15. SolanezumabStudy Group

    (2014) Phase 3 trials of solanezumab for mild-to-moderate Alzheimer's disease

    The New England Journal of Medicine 370:311–321.

    https://doi.org/10.1056/NEJMoa1312889

    • Google Scholar
11. 1. Drapeau E
    2. Mayo W
    3. Aurousseau C
    4. Le Moal M
    5. Piazza PV
    6. Abrous DN

    (2003) Spatial memory performances of aged rats in the water maze predict levels of hippocampal neurogenesis

    Proceedings of the National Academy of Sciences of USA 100:14385–14390.

    https://doi.org/10.1073/pnas.2334169100

    • Google Scholar
12. 1. Erickson KI
    2. Voss MW
    3. Prakash RS
    4. Basak C
    5. Szabo A
    6. Chaddock L
    7. Kim JS
    8. Heo S
    9. Alves H
    10. White SM
    11. Wojcicki TR
    12. Mailey E
    13. Vieira VJ
    14. Martin SA
    15. Pence BD
    16. Woods JA
    17. McAuley E
    18. Kramer AF

    (2011) Exercise training increases size of hippocampus and improves memory

    Proceedings of the National Academy of Sciences of USA 108:3017–3022.

    https://doi.org/10.1073/pnas.1015950108

    • Google Scholar
13. 1. Euston DR
    2. Gruber AJ
    3. McNaughton BL

    (2012) The role of medial prefrontal cortex in memory and decision making

    Neuron 76:1057–1070.

    https://doi.org/10.1016/j.neuron.2012.12.002

    • Google Scholar
14. 1. Frankland PW
    2. Bontempi B
    3. Talton LE
    4. Kaczmarek L
    5. Silva AJ

    (2004) The involvement of the anterior cingulate cortex in remote contextual fear memory

    Science 304:881–883.

    https://doi.org/10.1126/science.1094804

    • Google Scholar
15. 1. Gais S
    2. Albouy G
    3. Boly M
    4. Dang-Vu TT
    5. Darsaud A
    6. Desseilles M
    7. Rauchs G
    8. Schabus M
    9. Sterpenich V
    10. Vandewalle G
    11. Maquet P
    12. Peigneux P

    (2007) Sleep transforms the cerebral trace of declarative memories

    Proceedings of the National Academy of Sciences of USA 104:18778–18783.

    https://doi.org/10.1073/pnas.0705454104

    • Google Scholar
16. 1. Gaspar P
    2. Cases O
    3. Maroteaux L

    (2003) The developmental role of serotonin: news from mouse molecular genetics

    Nature Reviews Neuroscience 4:1002–1012.

    https://doi.org/10.1038/nrn1256

    • Google Scholar
17. 1. Gutman DA
    2. Holtzheimer PE
    3. Behrens TE
    4. Johansen-Berg H
    5. Mayberg HS

    (2009) A tractography analysis of two deep brain stimulation white matter targets for depression

    Biological Psychiatry 65:276–282.

    https://doi.org/10.1016/j.biopsych.2008.09.021

    • Google Scholar
18. 1. Hamani C
    2. Diwan M
    3. Isabella S
    4. Lozano AM
    5. Nobrega JN

    (2010a) Effects of different stimulation parameters on the antidepressant-like response of medial prefrontal cortex deep brain stimulation in rats

    Journal of Psychiatric Research 44:683–687.

    https://doi.org/10.1016/j.jpsychires.2009.12.010

    • Google Scholar
19. 1. Hamani C
    2. Diwan M
    3. Macedo CE
    4. Brandao ML
    5. Shumake J
    6. Gonzalez-Lima F
    7. Raymond R
    8. Lozano AM
    9. Fletcher PJ
    10. Nobrega JN

    (2010b) Antidepressant-like effects of medial prefrontal cortex deep brain stimulation in rats

    Biological Psychiatry 67:117–124.

    https://doi.org/10.1016/j.biopsych.2009.08.025

    • Google Scholar
20. 1. Hamani C
    2. Machado DC
    3. Hipolide DC
    4. Dubiela FP
    5. Suchecki D
    6. Macedo CE
    7. Tescarollo F
    8. Martins U
    9. Covolan L
    10. Nobrega JN

    (2012) Deep brain stimulation reverses anhedonic-like behavior in a chronic model of depression: role of serotonin and brain derived neurotrophic factor

    Biological Psychiatry 71:30–35.

    https://doi.org/10.1016/j.biopsych.2011.08.025

    • Google Scholar
21. 1. Hamani C
    2. McAndrews MP
    3. Cohn M
    4. Oh M
    5. Zumsteg D
    6. Shapiro CM
    7. Wennberg RA
    8. Lozano AM

    (2008) Memory enhancement induced by hypothalamic/fornix deep brain stimulation

    Annals of Neurology 63:119–123.

    https://doi.org/10.1002/ana.21295

    • Google Scholar
22. 1. Hamani C
    2. Stone SS
    3. Garten A
    4. Lozano AM
    5. Winocur G

    (2011) Memory rescue and enhanced neurogenesis following electrical stimulation of the anterior thalamus in rats treated with corticosterone

    Experimental Neurology 232:100–104.

    https://doi.org/10.1016/j.expneurol.2011.08.023

    • Google Scholar
23. 1. Herry C
    2. Garcia R

    (2002)

    Prefrontal cortex long-term potentiation, but not long-term depression, is associated with the maintenance of extinction of learned fear in mice

    The Journal of Neuroscience 22:577–583.

    • Google Scholar
24. 1. Hescham S
    2. Lim LW
    3. Jahanshahi A
    4. Blokland A
    5. Temel Y

    (2013a) Deep brain stimulation in dementia-related disorders

    Neuroscience and Biobehavioral Reviews 37:2666–2675.

    https://doi.org/10.1016/j.neubiorev.2013.09.002

    • Google Scholar
25. 1. Hescham S
    2. Lim LW
    3. Jahanshahi A
    4. Steinbusch HW
    5. Prickaerts J
    6. Blokland A
    7. Temel Y

    (2013b) Deep brain stimulation of the forniceal area enhances memory functions in experimental dementia: the role of stimulation parameters

    Brain Stimulation 6:72–77.

    https://doi.org/10.1016/j.brs.2012.01.008

    • Google Scholar
26. 1. Hestermann D
    2. Temel Y
    3. Blokland A
    4. Lim LW

    (2014) Acute serotonergic treatment changes the relation between anxiety and HPA-axis functioning and periaqueductal gray activation

    Behavioural Brain Research 273:155–165.

    https://doi.org/10.1016/j.bbr.2014.07.003

    • Google Scholar
27. 1. Ishikawa A
    2. Nakamura S

    (2003)

    Convergence and interaction of hippocampal and amygdalar projections within the prefrontal cortex in the rat

    The Journal of Neuroscience 23:9987–9995.

    • Google Scholar
28. 1. Jay TM
    2. Witter MP

    (1991) Distribution of hippocampal CA1 and subicular efferents in the prefrontal cortex of the rat studied by means of anterograde transport of Phaseolus vulgaris-leucoagglutinin

    The Journal of Comparative Neurology 313:574–586.

    https://doi.org/10.1002/cne.903130404

    • Google Scholar
29. 1. Jones MW
    2. Wilson MA

    (2005) Theta rhythms coordinate hippocampal-prefrontal interactions in a spatial memory task

    PLOS Biology 3:e402.

    https://doi.org/10.1371/journal.pbio.0030402

    • Google Scholar
30. 1. Kabbaj M
    2. Devine DP
    3. Savage VR
    4. Akil H

    (2000)

    Neurobiological correlates of individual differences in novelty-seeking behavior in the rat: differential expression of stress-related molecules

    The Journal of Neuroscience 20:6983–6988.

    • Google Scholar
31. 1. Kaczorowski CC
    2. Disterhoft JF

    (2009) Memory deficits are associated with impaired ability to modulate neuronal excitability in middle-aged mice

    Learning & Memory 16:362–366.

    https://doi.org/10.1101/lm.1365609

    • Google Scholar
32. 1. Kadar E
    2. Lim LW
    3. Carreras G
    4. Genis D
    5. Temel Y
    6. Huguet G

    (2011) High-frequency stimulation of the ventrolateral thalamus regulates gene expression in hippocampus, motor cortex and caudate-putamen

    Brain Research 1391:1–13.

    https://doi.org/10.1016/j.brainres.2011.03.059

    • Google Scholar
33. 1. Kennedy SH
    2. Giacobbe P
    3. Rizvi SJ
    4. Placenza FM
    5. Nishikawa Y
    6. Mayberg HS
    7. Lozano AM

    (2011) Deep brain stimulation for treatment-resistant depression: follow-up after 3 to 6 years

    The American Journal of Psychiatry 168:502–510.

    https://doi.org/10.1176/appi.ajp.2010.10081187

    • Google Scholar
34. 1. Kim KK
    2. Adelstein RS
    3. Kawamoto S

    (2009) Identification of neuronal nuclei (NeuN) as Fox-3, a new member of the Fox-1 gene family of splicing factors

    The Journal of Biological Chemistry 284:31052–31061.

    https://doi.org/10.1074/jbc.M109.052969

    • Google Scholar
35. 1. Kim KK
    2. Nam J
    3. Mukouyama YS
    4. Kawamoto S

    (2013) Rbfox3-regulated alternative splicing of Numb promotes neuronal differentiation during development

    The Journal of Cell Biology 200:443–458.

    https://doi.org/10.1083/jcb.201206146

    • Google Scholar
36. 1. Laroche S
    2. Davis S
    3. Jay TM

    (2000) Plasticity at hippocampal to prefrontal cortex synapses: dual roles in working memory and consolidation

    Hippocampus 10:438–446.

    https://doi.org/10.1002/1098-1063(2000)10:4<438::AID-HIPO10>3.0.CO;2-3

    • Google Scholar
37. 1. Laroche S
    2. Jay TM
    3. Thierry AM

    (1990) Long-term potentiation in the prefrontal cortex following stimulation of the hippocampal CA1/subicular region

    Neuroscience Letters 114:184–190.

    https://doi.org/10.1016/0304-3940(90)90069-L

    • Google Scholar
38. 1. Laxton AW
    2. Tang-Wai DF
    3. McAndrews MP
    4. Zumsteg D
    5. Wennberg R
    6. Keren R
    7. Wherrett J
    8. Naglie G
    9. Hamani C
    10. Smith GS
    11. Lozano AM

    (2010) A phase I trial of deep brain stimulation of memory circuits in Alzheimer's disease

    Annals of Neurology 68:521–534.

    https://doi.org/10.1002/ana.22089

    • Google Scholar
39. 1. Leon WC
    2. Bruno MA
    3. Allard S
    4. Nader K
    5. Cuello AC

    (2010) Engagement of the PFC in consolidation and recall of recent spatial memory

    Learning & Memory 17:297–305.

    https://doi.org/10.1101/lm.1804410

    • Google Scholar
40. 1. Lim LW
    2. Blokland A
    3. Tan S
    4. Vlamings R
    5. Sesia T
    6. Aziz-Mohammadi M
    7. Visser-Vandewalle V
    8. Steinbusch HW
    9. Schruers K
    10. Temel Y

    (2010) Attenuation of fear-like response by escitalopram treatment after electrical stimulation of the midbrain dorsolateral periaqueductal gray

    Experimental Neurology 226:293–300.

    https://doi.org/10.1016/j.expneurol.2010.08.035

    • Google Scholar
41. 1. Lim LW
    2. Janssen ML
    3. Kocabicak E
    4. Temel Y

    (2015a) The antidepressant effects of ventromedial prefrontal cortex stimulation is associated with neural activation in the medial part of the subthalamic nucleus

    Behavioural Brain Research 279:17–21.

    https://doi.org/10.1016/j.bbr.2014.11.008

    • Google Scholar
42. 1. Lim LW
    2. Prickaerts J
    3. Huguet G
    4. Kadar E
    5. Hartung H
    6. Sharp T
    7. Temel Y

    et al. (2015b) Electrical stimulation alleviates depressive-like behaviors of rats: Investigation of brain targets and potential mechanisms

    Trans Psychiatry 5:e535.

    https://doi.org/10.1038/tp.2015.24

    • Google Scholar
43. 1. Lim LW
    2. Temel Y
    3. Sesia T
    4. Vlamings R
    5. Visser-Vandewalle V
    6. Steinbusch HW
    7. Blokland A

    (2008) Buspirone induced acute and chronic changes of neural activation in the periaqueductal gray of rats

    Neuroscience 155:164–173.

    https://doi.org/10.1016/j.neuroscience.2008.05.038

    • Google Scholar
44. 1. Lim LW
    2. Temel Y
    3. Visser-Vandewalle V
    4. Blokland A
    5. Steinbusch H

    (2009) Fos immunoreactivity in the rat forebrain induced by electrical stimulation of the dorsolateral periaqueductal gray matter

    Journal of Chemical Neuroanatomy 38:83–96.

    https://doi.org/10.1016/j.jchemneu.2009.06.011

    • Google Scholar
45. 1. Lindberg O
    2. Westman E
    3. Karlsson S
    4. Ostberg P
    5. Svensson LA
    6. Simmons A
    7. Simmons A
    8. Wahlund LO

    (2012) Is the subcallosal medial prefrontal cortex a common site of atrophy in Alzheimer's disease and frontotemporal lobar degeneration?

    Frontiers in Aging Neuroscience 4:32.

    https://doi.org/10.3389/fnagi.2012.00032

    • Google Scholar
46. 1. Liu XS
    2. Chopp M
    3. Zhang RL
    4. Hozeska-Solgot A
    5. Gregg SC
    6. Buller B
    7. Lu M
    8. Zhang ZG

    (2009) Angiopoietin 2 mediates the differentiation and migration of neural progenitor cells in the subventricular zone after stroke

    The Journal of Biological Chemistry 284:22680–22689.

    https://doi.org/10.1074/jbc.M109.006551

    • Google Scholar
47. 1. Lobo A
    2. Launer LJ
    3. Fratiglioni L
    4. Andersen K
    5. Di Carlo A
    6. Breteler MM
    7. Copeland JR
    8. Dartigues JF
    9. Jagger C
    10. Martinez-Lage J
    11. Soininen H
    12. Hofman A

    (2000) Prevalence of dementia and major subtypes in Europe: a collaborative study of population-based cohorts. Neurologic Diseases in the Elderly Research Group

    Neurology 54:S4–S9.

    https://doi.org/10.1212/WNL.54.1.4

    • Google Scholar
48. 1. Lozano AM
    2. Mayberg HS
    3. Giacobbe P
    4. Hamani C
    5. Craddock RC
    6. Kennedy SH

    (2008) Subcallosal cingulate gyrus deep brain stimulation for treatment-resistant depression

    Biological Psychiatry 64:461–467.

    https://doi.org/10.1016/j.biopsych.2008.05.034

    • Google Scholar
49. 1. Lu B
    2. Chang JH

    (2004) Regulation of neurogenesis by neurotrophins: implications in hippocampus-dependent memory

    Neuron Glia Biology 1:377–384.

    https://doi.org/10.1017/S1740925X05000232

    • Google Scholar
50. 1. Maviel T
    2. Durkin TP
    3. Menzaghi F
    4. Bontempi B

    (2004) Sites of neocortical reorganization critical for remote spatial memory

    Science 305:96–99.

    https://doi.org/10.1126/science.1098180

    • Google Scholar
51. 1. Mayberg HS
    2. Lozano AM
    3. Voon V
    4. McNeely HE
    5. Seminowicz D
    6. Hamani C
    7. Schwalb JM
    8. Kennedy SH

    (2005) Deep brain stimulation for treatment-resistant depression

    Neuron 45:651–660.

    https://doi.org/10.1016/j.neuron.2005.02.014

    • Google Scholar
52. 1. Milad MR
    2. Quirk GJ

    (2002) Neurons in medial prefrontal cortex signal memory for fear extinction

    Nature 420:70–74.

    https://doi.org/10.1038/nature01138

    • Google Scholar
53. 1. Milad MR
    2. Vidal-Gonzalez I
    3. Quirk GJ

    (2004) Electrical stimulation of medial prefrontal cortex reduces conditioned fear in a temporally specific manner

    Behavioral Neuroscience 118:389–394.

    https://doi.org/10.1037/0735-7044.118.2.389

    • Google Scholar
54. 1. Ming G
    2. Henley J
    3. Tessier-Lavigne M
    4. Song H
    5. Poo M

    (2001) Electrical activity modulates growth cone guidance by diffusible factors

    Neuron 29:441–452.

    https://doi.org/10.1016/S0896-6273(01)00217-3

    • Google Scholar
55. 1. Nagai T
    2. Takuma K
    3. Kamei H
    4. Ito Y
    5. Nakamichi N
    6. Ibi D
    7. Nakanishi Y
    8. Murai M
    9. Mizoguchi H
    10. Nabeshima T
    11. Yamada K

    (2007) Dopamine D1 receptors regulate protein synthesis-dependent long-term recognition memory via extracellular signal-regulated kinase 1/2 in the prefrontal cortex

    Learning & Memory 14:117–125.

    https://doi.org/10.1101/lm.461407

    • Google Scholar
56. 1. Pang PT
    2. Teng HK
    3. Zaitsev E
    4. Woo NT
    5. Sakata K
    6. Zhen S
    7. Teng KK
    8. Yung WH
    9. Hempstead BL
    10. Lu B

    (2004) Cleavage of proBDNF by tPA/plasmin is essential for long-term hippocampal plasticity

    Science 306:487–491.

    https://doi.org/10.1126/science.1100135

    • Google Scholar
57. Book

    1. Paxinos G
    2. Watson C

    (1998)

    The rat brain in stereotaxic coordinates (4th edition)

    Academic Press.

    • Google Scholar
58. 1. Rex CS
    2. Kramár EA
    3. Colgin LL
    4. Lin B
    5. Gall CM
    6. Lynch G

    (2005) Long-term potentiation is impaired in middle-aged rats: regional specificity and reversal by adenosine receptor antagonists

    The Journal of Neuroscience 25:5956–5966.

    https://doi.org/10.1523/JNEUROSCI.0880-05.2005

    • Google Scholar
59. 1. Salat DH
    2. Kaye JA
    3. Janowsky JS

    (2001) Selective preservation and degeneration within the prefrontal cortex in aging and Alzheimer disease

    Archives of Neurology 58:1403–1408.

    https://doi.org/10.1001/archneur.58.9.1403

    • Google Scholar
60. 1. Salloway S
    2. Sperling R
    3. Fox NC
    4. Blennow K
    5. Klunk W
    6. Raskind M
    7. Sabbagh M
    8. Honig LS
    9. Porsteinsson AP
    10. Ferris S
    11. Reichert M
    12. Ketter N
    13. Nejadnik B
    14. Guenzler V
    15. Miloslavsky M
    16. Wang D
    17. Lu Y
    18. Lull J
    19. Tudor IC
    20. Liu E
    21. Grundman M
    22. Yuen E
    23. Black R
    24. Brashear HR
    25. Bapineuzumab 301 and 302 Clinical Trial Investigators

    (2014) Two phase 3 trials of bapineuzumab in mild-to-moderate Alzheimer's disease

    The New England Journal of Medicine 370:322–333.

    https://doi.org/10.1056/NEJMoa1304839

    • Google Scholar
61. 1. Sesia T
    2. Tan S
    3. Vlamings R
    4. Lim LW
    5. Visser-Vandewalle V
    6. Temel Y

    (2009) Basal ganglia and behaviour: behavioural effects of deep brain stimulation in experimental neurological and psychiatric disorders

    The Basal Ganglia IX 58:471–482.

    https://doi.org/10.1007/978-1-4419-0340-2_36

    • Google Scholar
62. 1. Shehadi K
    2. Maroun M

    (2012) Different effects of low frequency stimulation to infralimbic prefrontal cortex on extinction of aversive memories

    Brain Research 1490:111–116.

    https://doi.org/10.1016/j.brainres.2012.10.026

    • Google Scholar
63. 1. Shors TJ
    2. Miesegaes G
    3. Beylin A
    4. Zhao M
    5. Rydel T
    6. Gould E

    (2001) Neurogenesis in the adult is involved in the formation of trace memories

    Nature 410:372–376.

    https://doi.org/10.1038/35066584

    • Google Scholar
64. 1. Siapas AG
    2. Lubenov EV
    3. Wilson MA

    (2005) Prefrontal phase locking to hippocampal theta oscillations

    Neuron 46:141–151.

    https://doi.org/10.1016/j.neuron.2005.02.028

    • Google Scholar
65. 1. Sloane JA
    2. Pietropaolo MF
    3. Rosene DL
    4. Moss MB
    5. Peters A
    6. Kemper T
    7. Abraham CR

    (1997) Lack of correlation between plaque burden and cognition in the aged monkey

    Acta Neuropathologica 94:471–478.

    https://doi.org/10.1007/s004010050735

    • Google Scholar
66. 1. Stead JD
    2. Clinton S
    3. Neal C
    4. Schneider J
    5. Jama A
    6. Miller S
    7. Vazquez DM
    8. Watson SJ
    9. Akil H

    (2006) Selective breeding for divergence in novelty-seeking traits: heritability and enrichment in spontaneous anxiety-related behaviors

    Behavior Genetics 36:697–712.

    https://doi.org/10.1007/s10519-006-9058-7

    • Google Scholar
67. 1. Stern S
    2. Alberni C

    (2012) Mechanisms of memory enhancement

    Wiley interdisciplinary Reviews Systems Biology and Medicine 5:37–53.

    https://doi.org/10.1002/wsbm.1196

    • Google Scholar
68. 1. Stone SS
    2. Teixeira CM
    3. Devito LM
    4. Zaslavsky K
    5. Josselyn SA
    6. Lozano AM
    7. Frankland PW

    (2011) Stimulation of entorhinal cortex promotes adult neurogenesis and facilitates spatial memory

    The Journal of Neuroscience 31:13469–13484.

    https://doi.org/10.1523/JNEUROSCI.3100-11.2011

    • Google Scholar
69. 1. Suthana N
    2. Haneef Z
    3. Stern J
    4. Mukamel R
    5. Behnke E
    6. Knowlton B
    7. Fried I

    (2012) Memory enhancement and deep-brain stimulation of the entorhinal area

    The New England Journal of Medicine 366:502–510.

    https://doi.org/10.1056/NEJMoa1107212

    • Google Scholar
70. 1. Takashima A
    2. Jensen O
    3. Oostenveld R
    4. Maris E
    5. van de Coevering M
    6. Fernández G

    (2006a) Successful declarative memory formation is associated with ongoing activity during encoding in a distributed neocortical network related to working memory: a magnetoencephalography study

    Neuroscience 139:291–297.

    https://doi.org/10.1016/j.neuroscience.2005.05.067

    • Google Scholar
71. 1. Takashima A
    2. Petersson KM
    3. Rutters F
    4. Tendolkar I
    5. Jensen O
    6. Zwarts MJ
    7. McNaughton BL
    8. Fernández G

    (2006b) Declarative memory consolidation in humans: a prospective functional magnetic resonance imaging study

    Proceedings of the National Academy of Sciences of USA 103:756–761.

    https://doi.org/10.1073/pnas.0507774103

    • Google Scholar
72. 1. Tan S
    2. Vlamings R
    3. Lim L
    4. Sesia T
    5. Janssen ML
    6. Steinbusch HW
    7. Visser-Vandewalle V
    8. Temel Y

    (2010)

    Experimental deep brain stimulation in animal models

    1073–1079, Neurosurgery, 67, discussion1080, 10.1227/NEU.0b013e3181ee3580.

    • Google Scholar
73. 1. Teixeira CM
    2. Pomedli SR
    3. Maei HR
    4. Kee N
    5. Frankland PW

    (2006) Involvement of the anterior cingulate cortex in the expression of remote spatial memory

    The Journal of Neuroscience 26:7555–7564.

    https://doi.org/10.1523/JNEUROSCI.1068-06.2006

    • Google Scholar
74. 1. Temel Y
    2. Blokland A
    3. Lim LW

    (2012a) Deactivation of the parvalbumin-positive interneurons in the hippocampus after fear-like behaviour following electrical stimulation of the dorsolateral periaqueductal gray of rats

    Behavioural Brain Research 233:322–325.

    https://doi.org/10.1016/j.bbr.2012.05.029

    • Google Scholar
75. 1. Temel Y
    2. Hescham SA
    3. Jahanshahi A
    4. Janssen ML
    5. Tan SK
    6. van Overbeeke JJ
    7. Ackermans L
    8. Oosterloo M
    9. Duits A
    10. Leentjens AF
    11. Lim L

    (2012b) Neuromodulation in psychiatric disorders

    International Review of Neurobiology 107:283–314.

    https://doi.org/10.1016/B978-0-12-404706-8.00015-2

    • Google Scholar
76. 1. Temel Y
    2. Lim LW

    (2013) Neurosurgical treatments of depression

    Current Topics in Behavioral Neurosciences 14:327–339.

    https://doi.org/10.1007/7854_2012_222

    • Google Scholar
77. 1. Toda H
    2. Hamani C
    3. Fawcett AP
    4. Hutchison WD
    5. Lozano AM

    (2008) The regulation of adult rodent hippocampal neurogenesis by deep brain stimulation

    Journal of Neurosurgery 108:132–138.

    https://doi.org/10.3171/JNS/2008/108/01/0132

    • Google Scholar
78. 1. van Praag H
    2. Kempermann G
    3. Gage FH

    (1999) Running increases cell proliferation and neurogenesis in the adult mouse dentate gyrus

    Nature Neuroscience 2:266–270.

    https://doi.org/10.1038/6368

    • Google Scholar
79. 1. Vertes RP
    2. Hoover WB
    3. Szigeti-Buck K
    4. Leranth C

    (2007) Nucleus reuniens of the midline thalamus: link between the medial prefrontal cortex and the hippocampus

    Brain Research Bulletin 71:601–609.

    https://doi.org/10.1016/j.brainresbull.2006.12.002

    • Google Scholar
80. 1. Vyas A
    2. Bernal S
    3. Chattarji S

    (2003) Effects of chronic stress on dendritic arborization in the central and extended amygdala

    Brain Research 965:290–294.

    https://doi.org/10.1016/S0006-8993(02)04162-8

    • Google Scholar
81. 1. Ward MT
    2. Oler JA
    3. Markus EJ

    (1999) Hippocampal dysfunction during aging I: deficits in memory consolidation

    Neurobiology of Aging 20:363–372.

    https://doi.org/10.1016/S0197-4580(99)00045-7

    • Google Scholar
82. 1. Ying Z
    2. Covalin A
    3. Judy J
    4. Gomez-Pinilla F

    (2012) Hypothalamic stimulation enhances hippocampal BDNF plasticity in proportion to metabolic rate

    Brain Stimulation 5:642–646.

    https://doi.org/10.1016/j.brs.2011.11.001

    • Google Scholar

Author details

1. Albert Liu

   School of Biological Sciences, Nanyang Technological University, Singapore, Singapore

   Contribution

   AL, Analyzed parts of the behavioural and histochemical data

   Competing interests

   The authors declare that no competing interests exist.

2. Neeraj Jain

   School of Biological Sciences, Nanyang Technological University, Singapore, Singapore

   Contribution

   NJ, Conducted parts of the real-time PCR experiments

   Competing interests

   The authors declare that no competing interests exist.

3. Ajai Vyas

   School of Biological Sciences, Nanyang Technological University, Singapore, Singapore

   Contribution

   AV, Contributed to part of the data analysis and comments on the manuscript

   Competing interests

   The authors declare that no competing interests exist.

4. Lee Wei Lim

   1. School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
   2. Department of Biological Sciences, Sunway University, Bandar Sunway, Malaysia

   Contribution

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

   For correspondence

   drlimleewei@gmail.com

   Competing interests

   The authors declare that no competing interests exist.

• 6,481

  views

• 965

  downloads

• 64

  citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.