In the September 6 Neuron, researchers present electroencephalography (EEG) recordings of freely moving hAPP-transgenic mice that reveal evidence of spontaneous non-convulsive seizures. Surprisingly, while these abnormal discharges came on, the mice did not behave as if they were having an epileptic attack. They merely stopped while the electrical storm raged through their brain, and then continued scampering about in their cage. This observation forms the core of an ambitious paper that develops a new hypothesis for a contributing cause to the cognitive deficits in AD. The hypothesis proposes that Aβ-driven overexcitation of entorhinal-hippocampal circuits in turn leads to compensatory inhibitory changes in hippocampal networks, and that both processes together restrict synaptic plasticity and contribute to learning and memory deficits. Lennart Mucke at the Gladstone Institute of Neurological Disease in San Francisco, California, and his coworkers collaborated with epilepsy researcher Jeffrey Noebels of Baylor College of Medicine in Houston, Texas, for the study.

By characterizing epileptiform activity and associated changes in mouse models, the study draws attention to prior observations that people with AD have an elevated risk for seizures. This is known and has been reported as part of the clinical description of AD pedigrees and in epidemiological studies. Seizures occur especially at the early stages of AD and in autosomal-dominant early onset forms (eFAD). Even so, the human observation has not generated a focused research effort to date. The extent of the problem is currently unknown, in part because caregivers and doctors of people with AD might not notice abnormal brain discharges that stay below the level of the convulsive fits typically associated with epilepsy. Follow-up studies trying to suppress the spontaneous overexcitation with anticonvulsant drugs can test the hypothesis, and also might lead to new therapeutic approaches.

Continuing a research trend, the paper represents a departure from the field's long-standing focus on the historic twin pathologies of AD, i.e., amyloid plaques and neurofibrillary tangles. The word “plaque” appears only tangentially and the word “tangle” not at all, even though Aβ is seen as an upstream cause of all brain changes described and tau as playing a role, as well.

First author Jorge Palop and colleagues developed a hunch that aberrant network activities might be going on when they analyzed biochemical and anatomic changes in the dentate gyrus region of the hippocampus of mutant human APP-transgenic mice that produce high concentrations of Aβ peptide. The Mucke team and others had noticed reductions in the calcium-binding protein calbindin, the immediate-early gene Arc, changes in the phosphorylation of NMDA receptor subunits and other molecular changes that suggest that synaptic plasticity in the networks underlying memory was off. But there was a nagging paradox, in that some of these dentate gyrus alterations seemed to indicate increased neuronal activity and an excitotoxic reason for neurodegeneration, while at the same time the available data for Aβ's effect on synapses suggested that it decreases glutamatergic transmission, possibly by endocytosing AMPA or NMDA receptors. These coexisting clues to both excitotoxicity and synaptic suppression raised the questions of what the net effect of Aβ is. The present paper proposes that both overexcitation and subsequent inhibitory responses are at play.

The authors studied four lines expressing FAD mutant or wild-type human APP. In brief, hAPP FAD (J20) mice had molecular and circuit changes that indicate imbalances between excitatory and inhibitory neuronal activity in the hippocampus. These included increased expression of neuropeptide Y (NPY), axonal sprouting by interneurons, and alterations in the levels of NPY receptors—all in a pattern that suggested overexcitation. Moreover, the authors found increased excitatory mossy fiber innervation of GABAergic basket cells that inhibit these granule neurons. These changes overlap partly though not fully with known changes in epilepsy models. In epilepsy these neurons end up being less inhibited, whereas in the APP models they appear to be more strongly inhibited, and voltage-clamp recordings of the granule cells from J20 APP mice showed that they indeed have more frequent and high-amplitude miniature inhibitory post-synaptic currents (mIPSCs) than do control mice.

A tip-off that these changes might point to some sort of epileptiform activity came from previous research in that field. In an accompanying preview article, epilepsy researchers Soren Leonard and James McNamara of Duke University Medical Center in Durham, North Carolina, cite two prior studies that had found the same calbindin, NPY, and mIPSC changes in the dentate gyrus occurring a day after recurrent seizures in kindling models of epilepsy (Tonder et al., 1994; Nusser et al., 1998). These authors had postulated that the changes were a homeostatic response to the seizures. (Kindling refers to a phenomenon where repeated subconvulsive stimulation in a given area prompts the stimulated fibers to fire spontaneously afterwards; these "after discharges" can wax and sensitize the site of stimulation so that even a weak stimulus there days or weeks later can trigger a full-blown seizure. Kindling involves NMDA receptors and is thought to represent an underlying mechanism of chronic epilepsy.)

Pharmacologic experiments gave Palop and colleagues additional hints that the hippocampal changes in the APP-transgenic mice might be responses to overexcitation. In non-transgenic mice, injection of the excitatory amino acid kainate led to changes resembling those observed in APP mice, that is, increases in NPY, depletion of Arc and calbindin. By contrast, tau reduction prevented kainate-induced alterations in NPY. Recently, the Mucke lab had shown that reducing tau expression by half in the J20 improved cognition in these Aβ overexpressors and made them resistant to induced seizures (Roberson et al., 2007). In this study, coauthor Erik Roberson analyzed these bigenic mice further to show that they suffered neither NPY increase nor calbindin depletion. Together, these data suggested to the investigators that Aβ promotes neuronal excitation, and they conducted two types of experiment to test this notion.

First, Palop and colleagues challenged three different lines of mutant human APP mice with the GABA receptor antagonist pentylenetetrazole (PTZ). This triggered earlier and more severe seizures in all three transgenics than in wild-type controls. A specific difference within the J20 line tracked with the changes in the dentate gyrus: the most susceptible mice, which died from their seizures, had greater increases in NPY and losses of calbindin and Arc than did mice with less severe seizures or controls.

Secondly, the authors collaborated with Noebels' group to monitor EEG activity in six freely behaving adult J20 mice plus control mice with implanted electrodes. The recordings revealed generalized and synchronous discharges in all cortical electrodes in all transgenic but no control mice. Electrodes implanted more deeply into the hippocampus recorded similar discharges. Most striking among the abnormal discharges were non-convulsive seizures that started slow, accelerated, and then ended abruptly into a long cortical depression. During the seizures, the mice stayed still.

Further experiments confirmed that the sorts of synaptic alteration that the authors and other groups have previously linked to Aβ also occur in the dentate gyrus of the J20 mice analyzed for epileptiform activity. These include reduced phosphorylation of the NR2B subunit of NMDA receptors, and reduced levels of the GluR1 and GluR2 subunits of AMPA receptors. Finally, field EPSP recordings from hippocampal slices of these mice revealed synaptic plasticity deficits whose precise nature was specific to the circuit analyzed, suggesting that the dentate gyrus is supremely vulnerable to Aβ-induced network disruptions.

Overall, the authors take the spontaneous seizures to mean that the net effect of excess Aβ on the affected networks is excitatory, and that many of the observed alterations in the mice's brains likely reflect attempts of the networks to tamp down this overexcitation. Both these forces would eventually crimp the ability of entorhinal-hippocampal networks to retain new information. A question the present study leaves open is exactly how excess Aβ would “kindle” the excitability of the affected memory networks in the first place.

The similarities between J20 mice and epilepsy models go only so far, the authors emphasize. In the former, circuit changes tend to dampen granule cell excitability, whereas in the latter, circuit changes rev it up. In the J20 mice, and perhaps in AD, this tug-of-war between Aβ-driven excitation and compensatory inhibition might explain why overexcitation rarely escalates to fully fledged convulsive seizures yet still impairs cognitive function. Overt seizures are not a part of the typical clinical presentation of AD, and specific studies are needed to establish how common spontaneous epileptiform activity is in sporadic and familial AD, the authors state. Conceivably, such activity could explain the daily fluctuations in AD patients that caregivers know so well, where at times the loved one seems sharp but soon after may become confused and disoriented. If this work is independently confirmed, it also raises the prospect that some anticonvulsant drugs, many of which are available and widely used, might suppress the seizures and the depressions between seizures. If a drug does this, would it also prevent the molecular and circuit changes and, most importantly, the cognitive deficits? Both mouse and human studies to test this question are warranted, the authors conclude.—Gabrielle Strobel.


Palop JJ, Chin J, Roberson ED, Wang J, Thwin MT, Bien-Ly N, Yoo J, Ho KO, Yu GQ, Kreitzer A, Finkbeiner S, Noebels JL, Mucke L. Aberrant excitatory neuronal activity and compensatory remodeling of inhibitory hippocampal circuits in mouse models of Alzheimer's disease. Neuron. 2007 Sep 6;55(5):697-711. Abstract

Leonard AS, McNamara JO. Does epileptiform activity contribute to cognitive impairment in Alzheimer's disease? Neuron. 2007 Sep 6;55(5):677-8. Abstract

Q&A with Jorge Palop and Lennart Mucke. Questions by Gabrielle Strobel.

Q: What do the videotaped seizures in the mice look like?
A: It is a type of seizure activity that is not accompanied by the usual twitching and jerking movements seen in many forms of epilepsy. In fact, it took sophisticated brain wave recordings in freely behaving mice by electroencephalography (EEG) and telemetry to detect the seizure activity. These seizures are non-convulsive, so they cannot be easily detected by just watching the mice.

Q: How about in AD patients? Do people just stop what they were doing while a storm of epileptiform activity races through their cortex and hippocampus, then rest?
A: This possibility deserves to be explored. Transient episodes of amnestic wandering and disorientation in AD patients have been associated with epileptiform activity (Rabinowicz et al., 2000).

Q: What exactly is the news of your paper? People have known about seizures in AD patients, and at least some transgenic mouse data exist also.
A: Our paper shows that high levels of Aβ are sufficient to trigger abnormal overexcitation and compensatory inhibitory responses in the very brain networks that are responsible for learning and memory. Notably, most of the seizure activity was non-convulsive, which means it could easily be missed by clinical observations. The increased inhibitory activity we identified may explain why the overexcitation does not more frequently escalate into frank convulsive seizures in hAPP mice and AD patients. Our results also suggest that the suppression of the overexcitation might prevent and possibly even reverse cognitive impairments induced by high levels of Aβ.

Although many people in the field may not realize this, I believe that we were the first to demonstrate in hAPP-expressing hippocampal slices that Aβ inhibits glutamatergic synaptic transmission (Hsia et al., 1999). Subsequently, these findings were beautifully extended by other groups (Kamenetz et al., 2003; Hsieh et al., 2006; Shankar et al., 2007). Extrapolating from these findings, one might have predicted that Aβ decreases overall network activity. Yet, we found the opposite to be true. Several potential explanations were offered in our paper to reconcile these observations. Indeed, we demonstrated experimentally that epileptiform network activity can coexist with deficits in neurotransmission strength or plasticity at specific synapses.

Q: You describe epileptiform activity, presumably as a result of excess Aβ, and homeostatic compensatory reactions that constrain plasticity in learning and memory networks. Turning this around, do some people with epilepsy have learning impairments, and are they at higher risk for dementia?
A: Some people with epilepsy have learning impairments, but the etiology of these impairments is likely as complex as the etiology of epilepsy itself. We are unaware of dementia risk studies in people with epilepsy. Notably, our study suggests that the changes Aβ elicits in the brain overlap with epilepsy only partially, but not completely.

Q: You describe the inhibitory changes as compensation for prior overexcitation by Aβ. How does Aβ cause the original overexcitation? The clues that exist to date—about LTP, NMDAR, and AMPAR subunits—would seem to be inhibitory. In other words, what exactly touches off those spontaneous seizures?
A: We are pursuing this question very actively. As discussed in our study, there are at least three possible ways to reconcile the suppressive synaptic effects of Aβ with the overall network overexcitation we identified:

1. Depressed glutamatergic transmission may be a synaptic compensatory mechanism against overexcitation.
2. Inhibitory interneurons may be more susceptible to the suppressive effects of Aβ on glutamatergic synaptic transmission than excitatory principal neurons, leading to an overall increase in network excitability.
3. Cortical or subcortical regions that control neuronal excitability on a broad scale could be particularly susceptible to Aβ-induced impairments of glutamatergic synaptic transmission, increasing overall network excitability.

Q: Do your data suggest anticonvulsant drugs for treatment of AD?
A: Indeed, particularly during early stages of the disease and in cases with early onset.

Q: Valproate has been tried (ADCS trial; Porsteinsson, 2006), but there are many different anti-seizure drugs. What about others?
A: The valproate studies we are aware of have targeted primarily behavioral alterations in patients with relatively advanced disease. We are unaware of clinical trials of anticonvulsants for MCI and early AD. In addition, our ongoing studies suggest that some anticonvulsants may be better at suppressing Aβ-induced overexcitation than others. We are eager to extend these studies to human subjects.

Q: Are you, or other labs, now testing anticonvulsants in mutant hAPP mice?
A: We are and imagine that other labs will follow suit.

Q: Are seizures more common in FAD because this form of disease is most strongly driven by Aβ overproduction?
A: That is a possibility.

Q: APP- and presenilin-based FAD is rare. What makes your work relevant to sporadic AD?
A: The overlap between familial and sporadic appears wide at the clinical and pathological level. It is likely that there is also substantial overlap at the etiological level. Clearly, Aβ also accumulates to high levels in the brains of people with sporadic AD, and sporadic AD cases also have an increased incidence of seizures, as reviewed in our paper.

Q: In people with AD and MCI, how common is this subtle epileptiform activity?
A: We don't know, but are launching a clinical study to answer this important question.

Q: Where it does not rise to the level of a full-blown convulsive seizure, can it be quantified in people who are cognitively impaired and may be depressed and more passive than normal, as well?
A: Telemetry EEG recordings can be carried out also in humans and can detect seizure activity that is hard to detect clinically.

Q: There is a literature on using EEG to detect AD. Do these groups pick up on the epileptiform signals, or on different changes in EEG recordings?
A: Most EEG studies in AD have focused on frequency analysis, although there have been some reports of epileptiform activity, for example, the report by Rabinowicz et al., 2000 cited above.

Q: Might these groups have datasets already sitting in drawers and computers that would help get at the question of how frequent epileptiform activity is in AD?
A: This is a distinct possibility we would like to explore. Unfortunately, some AD patients with epilepsy have been excluded from EEG studies because it has not been widely appreciated that seizure activity may be part of the pathogenesis of this illness.

Q: More generally, does your study have any implications for the use of EEG in AD?
A: We think so, although we predict that special leads and sophisticated recording techniques may be required to monitor activity in the most relevant networks.

Q: Have you gotten feedback from epilepsy research groups to your data? What kind?
A: Jeff Noebels, coauthor of our paper, is an expert in epilepsy research in humans and mouse models. He was excited when we approached him about this collaboration and even more so when the EEG data started rolling in.

Q: What are the next steps?
A: We plan to use mouse models to identify drugs that can prevent and reverse Aβ-induced network dysfunction. We will also embark on clinical studies to determine if our results and conclusions are relevant to people with AD.


  1. This is an interesting paper coming from an excellent research group. I agree that neural networks and synaptic plasticity are at the center of Alzheimer disease (Ashford and Teter, 2002), but in interpreting the relevance of this study to AD, we should also keep several issues in mind. This work is in mice, which only model a small part of the Alzheimer pathology. Further, β amyloid is associated with vulnerability to Alzheimer disease, but the dementia is due to a tauopathy, so any potential connection between Aβ and tau effects hinted at in the bigenic mice needs to be more specifically explored.

    In my clinical experience, the epileptic issues in AD are less than described here. Alzheimer patients rarely have seizures, and the ones we reported in the literature were related to anti-cholinesterase drugs (Piecoro et al., 1998).

    The concept of looking at a whole neural network and seeing how it responds to amyloid stress is very interesting. At the same time, the development of the plaques and tangles seems to be more of a local phenomenon affecting components of the network than a problem at the system level of networks.

    I was a coauthor on a paper cited in this study (Mark et al., 1995). We were not primarily interested in seizures. Rather, our idea was that excitotoxicity would stress neuroplastic mechanisms (possibly involving GSK3) and exacerbate Alzheimer pathology development—which might in turn be reduced by valproate. Valproate seemed potentially useful because it is known to affect the brain. Along these lines, it could be considered that β amyloid could increase the excitability in neural networks, and reduction of that excitability could reduce the predilection for tauopathy to develop. We clearly need more data. At this point, it still remains doubtful to me that that increase of excitability is the hallmark of the amyloid pathologic mechanism.


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    View all comments by John (Wes) Ashford
  2. Comment by Jorge J. Palop and Lennart Mucke
    We completely agree with Dr. Ashford in that the specific connection between Aβ and tau revealed by this and our previous study (Roberson et al., 2007) deserves to be explored further. However, we believe that the potential role of Aβ-induced aberrant overexcitation in the pathogenesis of AD may have been underestimated.

    As highlighted by our study, much of such activity is non-convulsive and, thus, could easily escape detection by standard clinical exams. Our study also revealed a striking compensatory remodeling and activation of inhibitory circuits, which could account for the fact that obvious convulsive seizures are not frequent in this condition.

    However, convulsive seizures are probably more frequent in AD than many clinicians realize. As discussed in our paper, AD patients clearly have a higher incidence of seizures than reference populations (Amatniek et al., 2006; Hauser et al., 1986; Hesdorffer et al., 1996; Lozsadi and Larner, 2006; Mendez and Lim, 2003).

    Interestingly, the risk of epileptic activity is particularly high in AD patients with early onset dementia and during the earlier stages of the disease, reaching an 87-fold increase in seizure incidence compared with an age-matched reference population (Amatniek et al., 2006; Mendez et al., 1994). Thus, aberrant neuronal overexcitation may play an important role not only in hAPP mouse models, but also in the pathogenesis of dementia in sporadic AD.

    Indeed, epileptiform activity has been associated with transient episodes of amnestic wandering and disorientation in AD (Rabinowicz et al., 2000). It is interesting in this regard that the relationship between seizures and AD is even tighter in autosomal-dominant early onset FAD. Pedigrees with epilepsy have been identified in FAD linked to mutations in presenilin-1, presenilin-2, and APP (Edwards-Lee et al., 2005; Marcon et al., 2004; Snider et al., 2005). More than 30 different mutations in presenilin-1 are associated with seizures (Larner and Doran, 2006). Our results suggest that the increased epileptic activity in sporadic and autosomal-dominant AD may be caused by Aβ-induced increases in network excitability. Future studies will need to test the hypothesis that this alteration contributes critically to the pathogenesis of AD, objectively and without preconceived notions about outcomes.


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  3. This is a significant advance in understanding how networks are affected in AD. The recent report by Kim et al. that the α-, β-, and γ-secretases process, and regulate expression and function of, the β2 subunit of voltage-sensitive sodium channels suggests that widespread changes in neuronal excitability in AD may have a more fundamental explanation than effects on transmitter receptors.


    . BACE1 regulates voltage-gated sodium channels and neuronal activity. Nat Cell Biol. 2007 Jul;9(7):755-64. PubMed.

  4. Palop et al. clearly demonstrate neural network dysfunction in hAPPFAD-mice. Our recent study also supports neural network dysfunction in AD patients, as a consequence of elevated BACE1 activity rather than a direct effect of increased Aβ levels. We found that BACE1 regulates voltage-gated sodium channel levels and surface expression through processing of its β2 subunit (Kim et al., 2007). In particular, increased BACE1 activity reduces surface Nav1.1 sodium channel expression and sodium current by 50 percent in hippocampal neurons from BACE1-transgenic mice as compared to wild-type controls. Haploinsufficiency of Nav1.1 induces epileptic seizures in mouse and human by preferentially decreasing sodium currents in GABAergic inhibitory neurons (Yu et al., 2006; for humans, see a review by Meisler and Kearney, 2005). For this reason, we predicted that elevated BACE1 activity in AD would alter sodium channel metabolism, leading to neural network dysfunctions such as seizures (Kim et al., 2007).

    It will be interesting to examine the specific contribution of the two pathways to neural network dysfunction in AD patients: one via elevated BACE1 activity leading to voltage-gated sodium channel dysfunction, the other via elevated Aβ with unclear molecular mechanism. These two pathways may be separate, both contributing to network dysfunction in AD patients. The former may affect membrane excitability/neuronal activity in the axons, soma, and dendrites of neuronal cells while the latter may directly affect synapses. However, they can also interact with each other. Zhao et al. recently reported that amyloid plaques induce BACE1 in surrounding neurons in mice and AD brains (Zhao et al., 2007). Therefore, elevated BACE1 by Aβ plaques could also contribute to network dysfunction and non-convulsive seizure activities by altering sodium channel metabolism. Elevated BACE1 activity increases Aβ generation in AD patients as well as sodium channel dysfunction, both of which can synergistically contribute to the network dysfunction. The interaction of these two pathways will be an interesting subject to explore in relation to AD pathogenesis.


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  5. This article raises a number of interesting issues with regard to improving the understanding and treatment of Alzheimer disease (AD). The authors demonstrate that β amyloid aberrantly increased neuronal excitability in cortex and hippocampus, which led to a series of neuronal structural and electrophysiologic alterations in the entorhinal cortex and hippocampus that are found in AD pathology. Such β amyloid-induced changes were either genetically induced in transgenic mouse models of AD, or exogenously induced by kainic acid administration in non-transgenic mice. Furthermore, reduction of neuronal tau structural microtubular proteins reduced the amount of disruption. The authors also showed that these animals exhibited abnormal excitatory EEG activity from cortical and hippocampal electrodes, often without clinically overt seizure activity.

    The relevance of these basic research findings to treatment of AD patients is that EEG activity may be a useful marker for the expression and treatment-mediated control of these pathophysiologic changes. The EEG signature from scalp electrodes will certainly appear different from that produced by cortical and hippocampal electrodes, as well as from that produced by hippocampal slice recordings. Even so, there is almost certain to be a scalp signature that can be identified with the appropriate EEG analytical methodology (Sneddon et al., 2005). The nature of the scalp EEG signature could be studied by performing scalp recordings in animals who have also had cortical and hippocampal recordings, and by performing hippocampal and cortical plus scalp electrode recordings in AD or perhaps epileptic patients.

    Such a scalp EEG signature, once identified by proper EEG analytic methodology, would serve as a useful index of how well a given treatment is retarding AD pathophysiology. This is particularly relevant now that clinically safe β amyloid-lowering agents have been developed and may be FDA-approved soon. While reversal of cognitive and functional impairment in AD would be optimal, it is much more likely that treatment will delay or perhaps halt AD progression, such that an EEG measure of the degree to which this occurs could help guide physicians in optimizing each patient's treatment.

    Such an EEG tool would certainly be useful in deciding whether to continue therapy with memantine (Namenda) and with cholinesterase inhibitors in very mildly impaired AD patients. In many cases, there is no clear symptomatic improvement. Because evidence exists both for and against disease-delaying effects for cholinesterase inhibitors (Farlow et al., 2005; Geldmacher et al., 2006; Doody et al., 2001; Raskind et al., 2004; Birks et al., 2006) and for NMDA receptor modulators (i.e., memantine) (Kirby et al., 2006; Bullock 2006), it is useful to identify potential disease-delaying effects in each patient. Given findings by Palop et al. about aberrant neuronal excitatory activity contributing to the progression of AD pathophysiology, it would be important to know if memantine, which minimizes aberrant excitatory glutamatergic activity and may reduce the formation of abnormally phosphorylated tau protein (Degerman Gunnarsson et al., 2007), is forestalling the progression of AD pathophysiology even if symptoms do not improve. Similarly, given the recent findings that cholinesterase inhibitors can beneficially modulate amyloid precursor protein metabolism to potentially reduce β amyloid formation in AD (Nordberg, 2006), and that the three FDA-approved cholinesterase inhibitors have different mechanisms and different potencies in this regard, it would be useful to be able to measure the effect of a given cholinesterase inhibitor on the AD pathophysiology of a given patient. Such translational research from cortical and hippocampal electrophysiology to scalp EEG recordings could have substantial benefits for AD patients and their treating physicians.


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    View all comments by William Rodman Shankle

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Paper Citations

  1. . Kindling induces transient changes in neuronal expression of somatostatin, neuropeptide Y, and calbindin in adult rat hippocampus and fascia dentata. Epilepsia. 1994 Nov-Dec;35(6):1299-308. PubMed.
  2. . Increased number of synaptic GABA(A) receptors underlies potentiation at hippocampal inhibitory synapses. Nature. 1998 Sep 10;395(6698):172-7. PubMed.
  3. . Reducing endogenous tau ameliorates amyloid beta-induced deficits in an Alzheimer's disease mouse model. Science. 2007 May 4;316(5825):750-4. PubMed.
  4. . Aberrant excitatory neuronal activity and compensatory remodeling of inhibitory hippocampal circuits in mouse models of Alzheimer's disease. Neuron. 2007 Sep 6;55(5):697-711. PubMed.
  5. . Does epileptiform activity contribute to cognitive impairment in Alzheimer's disease?. Neuron. 2007 Sep 6;55(5):677-8. PubMed.
  6. . Transient epileptic amnesia in dementia: a treatable unrecognized cause of episodic amnestic wandering. Alzheimer Dis Assoc Disord. 2000 Oct-Dec;14(4):231-3. PubMed.
  7. . Plaque-independent disruption of neural circuits in Alzheimer's disease mouse models. Proc Natl Acad Sci U S A. 1999 Mar 16;96(6):3228-33. PubMed.
  8. . APP processing and synaptic function. Neuron. 2003 Mar 27;37(6):925-37. PubMed.
  9. . AMPAR removal underlies Abeta-induced synaptic depression and dendritic spine loss. Neuron. 2006 Dec 7;52(5):831-43. PubMed.
  10. . Natural oligomers of the Alzheimer amyloid-beta protein induce reversible synapse loss by modulating an NMDA-type glutamate receptor-dependent signaling pathway. J Neurosci. 2007 Mar 14;27(11):2866-75. PubMed.
  11. . Divalproex sodium for the treatment of behavioural problems associated with dementia in the elderly. Drugs Aging. 2006;23(11):877-86. PubMed.

Other Citations

  1. hAPP FAD (J20) mice

External Citations

  1. ADCS trial

Further Reading

No Available Further Reading

Primary Papers

  1. . Aberrant excitatory neuronal activity and compensatory remodeling of inhibitory hippocampal circuits in mouse models of Alzheimer's disease. Neuron. 2007 Sep 6;55(5):697-711. PubMed.
  2. . Does epileptiform activity contribute to cognitive impairment in Alzheimer's disease?. Neuron. 2007 Sep 6;55(5):677-8. PubMed.