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Flavonoids as modulators of memory and learning: molecular interactions resulting in behavioural effects

Published online by Cambridge University Press:  14 March 2012

Catarina Rendeiro
Affiliation:
Molecular Nutrition Group, School of Chemistry, Food and Pharmacy, University of Reading, Reading RG6 6AP, UK School of Psychology and Clinical Language Sciences, University of Reading, Reading RG6 6AL, UK
João D. T. Guerreiro
Affiliation:
Institute for Biotechnology and Bioengineering, Centre for Biological and Chemical Engineering, IST, Lisboa, Portugal
Claire M. Williams
Affiliation:
School of Psychology and Clinical Language Sciences, University of Reading, Reading RG6 6AL, UK
Jeremy P. E. Spencer*
Affiliation:
Molecular Nutrition Group, School of Chemistry, Food and Pharmacy, University of Reading, Reading RG6 6AP, UK
*
*Corresponding author: Professor Jeremy P. E. Spencer, fax +44 0118 931 0080, email: [email protected]
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Abstract

There is considerable interest in the potential of a group of dietary-derived phytochemicals known as flavonoids in modulating neuronal function and thereby influencing memory, learning and cognitive function. The present review begins by detailing the molecular events that underlie the acquisition and consolidation of new memories in the brain in order to provide a critical background to understanding the impact of flavonoid-rich diets or pure flavonoids on memory. Data suggests that despite limited brain bioavailability, dietary supplementation with flavonoid-rich foods, such as blueberry, green tea and Ginkgo biloba lead to significant reversals of age-related deficits on spatial memory and learning. Furthermore, animal and cellular studies suggest that the mechanisms underpinning their ability to induce improvements in memory are linked to the potential of absorbed flavonoids and their metabolites to interact with and modulate critical signalling pathways, transcription factors and gene and/or protein expression which control memory and learning processes in the hippocampus; the brain structure where spatial learning occurs. Overall, current evidence suggests that human translation of these animal investigations are warranted, as are further studies, to better understand the precise cause-and-effect relationship between flavonoid intake and cognitive outputs.

Type
70th Anniversary Conference on ‘From plough through practice to policy’
Copyright
Copyright © The Authors 2012

Abbreviations:
AD

Alzheimer's disease

Akt

protein kinase B

BDNF

brain-derived neurotrophic factor

CREB

cAMP response element binding protein

EC

epicatechin

EGC

epigallocatechin

ERK

extracellular-signal-regulated kinase

GB

Ginkgo biloba

LTP

long-term potentiation

MWM

Morris Water Maze

PKC

protein kinase C

Diet is an important lifestyle factor, which in recent times has been investigated for its influence on cognitive function and the incidence and onset of neurodegenerative disorders(Reference Parrott and Greenwood1, Reference Gomez-Pinilla2). It has long been known that a diet high in saturated fats negatively impacts on cognitive processing and increases the risk of neurological dysfunction in both animals and human subjects(Reference Greenwood and Winocur3, Reference Molteni, Barnard and Ying4), while energy restriction (reduction in approximately 30% energy intake) protects the brain from injury(Reference Ingram, Weindruch and Spangler5, Reference Johnson, Summer and Cutler6). Recently, significant evidence has emerged to indicate that phytochemical-rich foods, and in particular those rich in flavonoids, may reverse age-related deficits in cognitive function in both animals and human subjects(Reference Letenneur, Proust-Lima and Le Gouge7Reference Beking and Vieira9). For example, the PAQUID prospective study examined cognitive performance in 1640 subjects (aged at least 65 years and cognitively normal at baseline) on four occasions over a 10-year-period and found that flavonoid-intake was associated with a significantly better cognitive performance over time(Reference Letenneur, Proust-Lima and Le Gouge7) (P=0·046). Furthermore, a cross-sectional study examining the relationship between the intake of three common flavonoid-containing foods (chocolate, wine and tea) and cognitive performance in elderly individuals revealed that there was a dose-dependent, positive relationship between the intake of these foods and performance on multiple cognitive outcomes (Kendrick Object Learning Test, Digit Symbol Test, Block Design, Mini-Mental State Examination and Controlled Oral Word Association Test)(Reference Nurk, Refsum and Drevon10). More recently, the consumption of dietary flavonoids, especially flavonols (in twenty-three different developed countries) has been shown to be associated with lower rates of dementia(Reference Beking and Vieira9).

In agreement with this observational data, a large number of dietary intervention studies in both human subjects and animals, in particular those using flavonoid-rich foods or beverages derived from Camellia sinensis (tea)(Reference Chan, Hosoda and Tsai11Reference Unno, Takabayashi and Yoshida16)Ginkgo biloba (GB)(Reference Oliveira, Sanada and Saragossa Filho17Reference Itil, Eralp and Ahmed20), Theobroma cacao (cocoa)(Reference Fisher, Sorond and Hollenberg21Reference Dinges23) and Vaccinium spp. (blueberry)(Reference Williams, El Mohsen and Vauzour24Reference Krikorian, Shidler and Nash28) have similarly demonstrated beneficial effects on memory and learning. Although there is evidence suggesting that these diets are capable of inducing improvements in cognitive function by protecting vulnerable neurons, enhancing existing neuronal function or by stimulating neuronal regeneration(Reference Mandel and Youdim29Reference Shukitt-Hale, Carey, Joseph and Prasad32), the precise mechanisms by which these compounds act in the brain are not fully established.

In order to effectively investigate the precise mechanisms by which flavonoids influence memory, learning and other cognitive processes, we must first consider how the memory works, including how such processes are controlled at the molecular level to facilitate acquisition and storage of sensory information as short- and long-term memory. Furthermore, how such information is processed in the hippocampus during specific cognitive events, such as the learning of spatial task information, will be illustrated. In particular, the roles that specific hippocampal regions play in the acquisition, consolidation and retrieval of information will help to elucidate how flavonoids are capable of exerting their specific cognitive improvements following supplementation. Lastly, the review will describe the various datasets from rodent studies that have investigated the impact of chronic supplementation with flavonoid-rich foods and/or beverages (green tea, blueberries and GB) and pure flavonoids on spatial memory and how that impacts on specific learning-related molecular events in the brain. Overall, a better understanding of the molecular basis underpinning the effects of flavonoid-rich foods on cognition will help us to determine how best to manipulate diet in order to increase the resistance of neurons to insults and promote mental fitness.

Flavonoids: dietary sources and bioavailability

Flavonoids comprise the most common group of polyphenolic compounds in the human diet. Recent data show that the daily flavonoid intake per-capita is estimated to be about 182 mg in the UK and 177 mg in Ireland(Reference Beking and Vieira33). The major sources of flavonoids include fruits, vegetables, tea, wine and cocoa(Reference Harnly, Doherty and Beecher34). They may be divided into different subclasses according to the degree of oxidation of the heterocyclic ring, the hydroxylation pattern of the ring structure and the substitution in the three-position. Accordingly, the main dietary groups of flavonoids are: (1) anthocyanins whose main sources include red wine and berry fruits; (2) flavanols, found in green tea, red wine, cocoa; (3) flavonols found in onions, leeks and broccoli; (4) flavones which are abundant in parsley and celery; (5) isoflavones, typically found in soya and soya products and (6) flavanones which are mainly found in citrus fruits and tomatoes (Table 1). It has been reported that anthocyanins and flavanols may account for approximately 65% of the total consumption of flavonoids in the UK(Reference Beking and Vieira33). In general, flavonoids in foods exist as hydroxylated, methoxylated and/or glycosylated derivatives (except for catechins)(Reference Rice-Evans, Miller and Paganga35, Reference Scalbert and Williamson36) and are linked to a sugar moiety that is often glucose or rhamnose.

Table 1. Structure of the main flavonoids present in the human diet

Once ingested, flavonoids undergo extensive phase I and II metabolism in the small and large intestine, in the liver and in cells, resulting in very different forms in the body to those found in food itself(Reference Manach, Scalbert and Morand37Reference Crozier, Jaganath and Clifford40). Accordingly, all classes of flavonoids undergo extensive metabolism in the jejunum and ileum of the small intestine, with the resulting metabolites entering the portal vein where they will subsequently undergo further metabolism in the liver (Fig. 1). As mentioned, dietary flavonoids are substrates for phase I (hydrolysing and oxidising) and phase II (conjugating and detoxifying) enzymes, being de-glucosylated and metabolised into glucuronides, sulphates and O-methylated derivatives(Reference Scalbert and Williamson36, Reference Spencer, Chowrimootoo and Choudhury39, Reference Spencer41, Reference Crozier, Del Rio and Clifford42). For instance, green tea catechins are typically metabolised in the liver to glucuronides, sulphates and O-methylated derivatives of these conjugates(Reference Stalmach, Mullen and Steiling43Reference Del Rio, Borges and Crozier45). On the other hand, anthocyanins, unlike other flavonoids, do not appear to undergo extensive phase I and II metabolism of the parent anthocyanidin(Reference Kay46). Rather, only a relatively small percentage (<2%) of the parent compounds are detected in the blood or in the urine within 24 h of consumption(Reference Mazza, Kay and Cottrell47Reference Sakakibara, Ogawa and Koyanagi50), suggesting a poor absorption of these compounds and/or their decomposition in the neutral or alkaline conditions of the small intestine(Reference Kay, Kroon and Cassidy51). However, experiments in ileostomy patients (lacking a colon) have suggested that up to 85% of anthocyanins from blueberry may traverse the small intestine intact, indicating that under normal physiological conditions a high amount of anthocyanins may reach the large intestine intact(Reference Kahle, Kraus and Scheppach52).

Fig. 1. Summary of the formation of metabolites and conjugates of flavonoids in human subjects. All classes of flavonoids undergo extensive phase II metabolism in the gastrointestinal tract and liver during which there is significant glucuronidation and sulfation of nearly all flavonoids by the action of uridine diphosphate-glucuronosyltransferase and sulfotransferase enzymes, respectively. There is also extensive O-methylation catalysed by the action of catechol-O-methyltransferase. Colonic microflora degrades flavonoids into smaller phenolic acids, such as phenylacetic acid, protocatechuic acid, phenylpropionic acid and benzoic acid, which may also be absorbed. Some of these metabolites are excreted through the kidneys. However, some may enter peripheral cells (e.g endothelial cells) and cross the blood–brain barrier and enter the brain. Flavonoids may then undergo further intracellular metabolism (phase III), usually oxidative metabolism, P450-related metabolism and conjugation with thiols.

Although absorption is traditionally associated with the small intestine, the colon is also capable of absorbing many micronutrients. This process may involve their initial chemical or microbial transformation. Flavonoids are known to undergo extensive metabolism in the colon, in particular by gut microbiota which induce their breakdown to phenolic acids(Reference Scalbert, Morand and Manach38, Reference Spencer, Abd El Mohsen and Minihane53) (Fig. 1). The microbiota catalyse this breakdown of the flavonoid structure in two steps, first by removing the conjugated moiety (formed in the small intestine) and second by cleaving the flavonoid backbone structure, usually across the A-ring. Many of these catabolites are efficiently absorbed in the colon, appear in the blood and are ultimately excreted in the urine. For example, in vitro studies have indicated that protocatechuic acid is one of the major bacterial degradation products of anthocyanins(Reference Aura, Martin-Lopez and O'Leary54) and may be found in rat plasma after feeding cyanidin-3-O-glucoside(Reference Tsuda, Horio and Osawa55). In a human intervention study involving orange-juice supplementation, protocatechuic acid was also the main product found in the blood and was estimated to account for up to 70% of total anthocyanin intake(Reference Vitaglione, Donnarumma and Napolitano56). Altogether, there is evidence to suggest that degradation products, such as protocatechuic acid, may be present in tissues at higher concentrations than the parent anthocyanidin. Therefore, it is clear that both the small intestinal conjugates of flavonoids and the bacterial-derived products formed in the colon are likely to contribute, at least in part, to the biological activities ascribed to anthocyanins and other flavonoids in vivo (Reference Williamson and Clifford57).

Bioavailability of flavonoids in the brain

In order for flavonoids to directly influence brain function, they must cross the blood–brain barrier (Reference Milbury and Kalt58) (Fig. 1). The extent of their blood–brain barrier penetration has been shown to be dependent on the lipophilicity of the compound(Reference Youdim, Dobbie and Kuhnle59). In theory, O-methylated flavonoid metabolites should be able to access the brain more easily than the more polar flavonoid glucuronides, although some drug glucuronides can cross the blood–brain barrier(Reference Aasmundstad, Morland and Paulsen60) and exert pharmacological effects(Reference Sperker, Backman and Kroemer61). The flavanol epigallocatechin (EGC) gallate, a relatively polar flavanol, has been reported to enter the brain after the gastric administration of (3H)-EGC gallate(Reference Suganuma, Okabe and Oniyama62). Similarly, the flavanols EGC gallate and epicatechin (EC)(Reference Suganuma, Okabe and Oniyama62, Reference Abd El Mohsen, Kuhnle and Rechner63), as well as anthocyanins(Reference Talavera, Felgines and Texier64) such as pelargonidin(Reference El Mohsen, Marks and Kuhnle65), have all been found in the brain after oral administration. Furthermore, flavanones have also been found in rodent brain following intravenous administration(Reference Peng, Cheng and Huang66).

With regard to specific brain localisation, several studies report anthocyanins in different regions of the brain of both rodents and pigs after supplementation with blueberry(Reference Milbury and Kalt58, Reference Andres-Lacueva, Shukitt-Hale and Galli67, Reference Kalt, Blumberg and McDonald68) and grape extract(Reference Passamonti, Vrhovsek and Vanzo69) and (−)-EC and its O-methylated derivatives have been shown in the brains of mice supplemented with the pure compound for 2 weeks(Reference van Praag, Lucero and Yeo70). Lastly, a 12-week blueberry supplementation was shown to result in accumulation of anthocyanins and flavanols in both the hippocampus and cortex(Reference Williams, El Mohsen and Vauzour24), with the total amounts of flavanols (including flavanol metabolites) being much higher than that of anthocyanins despite blueberry being higher in the latter. This confirms previous data suggesting that flavanols are more bioavailable than anthocyanins after oral administration (reviewed in(Reference Del Rio, Borges and Crozier45)).

Memory and learning

Spatial memory and its localisation in the brain

Learning and memory are two related processes by which information about the world (collected through sensory apparatus) is acquired, stored and later retrieved in the brain. There are two major types of memory: (1) declarative or explicit memory, which is designed to represent objects and events in the external world, as well as the relationships between them and (2) non-declarative or implicit memory, which is related with perceptual-motor skills and habits. The main difference between these is that while the retrieval of declarative memories requires conscious attention, non-declarative memories can be retrieved without conscious recollection(Reference Squire and Zola71). These two parallel memory systems are dependent on different brain structures. Declarative memories are dependent on the integrity of the hippocampus, while non-declarative or implicit memories depend upon the integrity of structures such as amygdala and striatum(Reference Squire and Zola71, Reference Squire and Kandel72). Early discoveries in amnesic patients, such as the widely known ‘patient HM’, showed an important role for the hippocampus in the process of consolidating labile short-term explicit memories into a more stable form, the so-called long-term memory(Reference Cohen and Eichenbaum73). It is also widely accepted that repeated exposure to sensory information, i.e. via repetition or training, helps during the consolidation process of converting short-term memories into long-term ones(Reference Lechner, Squire and Byrne74, Reference Kandel and Squire75). Since these first observations, an extensive body of research has shown that disruption of the hippocampus primarily affects recently formed memories, but does not impair recollection of remote memories, believed to be stored in the neocortex. Thus, there is a general consensus that the hippocampus plays a time-limited role in learning processes, being particularly involved in the acquisition and the consolidation of memories(Reference Frankland and Bontempi76Reference Zola-Morgan and Squire78).

A particular aspect of declarative memory that has been used to access the effects of flavonoid-rich diets on behaviour is spatial memory. Spatial memory is well characterised in both rodents and human subjects and it is dependent on the hippocampus in both(Reference King, Burgess and Hartley79Reference Shrager, Bayley and Bontempi83). Rodents provide a good model in which to test spatial memory as they have an impressive ability to orientate themselves within a novel environment and can remember complex relationships between visuospatial cues in a way similar to human subjects(Reference Kesner and Hopkins84, Reference Astur, Taylor and Mamelak85). As such, several maze environments, most notably the Radial Arm Maze(Reference Olton and Samuelson86) and Morris Water Maze (MWM)(Reference Morris87) have been developed to assess rodent spatial memory and learning. There is direct evidence that such spatial memory tasks are sensitive to hippocampal injury, suggesting that these are good models in which to access spatial memory in rodents(Reference Olton and Papas88Reference Bannerman, Yee and Good90). In addition, it has been comprehensively reported that rats show distinct age-related deficits in spatial learning tasks, in a manner similar to those observed for human subjects in equivalent ‘human’ spatial memory tasks(Reference Barnes, Boller and Grafman91Reference Wilson, Ikonen and Gallagher95). Thus, spatial memory constitutes an excellent model in which to evaluate the potential of flavonoids to reverse age-related cognitive deficits. To date, the majority of studies investigating the impact of flavonoid-rich diets on cognition have focused on spatial memory in either healthy, aged animals or senescence-accelerated animal models(Reference Williams, El Mohsen and Vauzour24, Reference Casadesus, Shukitt-Hale and Stellwagen25, Reference Joseph, Shukitt-Hale and Denisova27, Reference Li, Zhao and Zhang96).

Molecular basis of memory

It is widely accepted that the process of learning involves reversible changes in synaptic transmission within hippocampal neuronal circuitry which once stabilised, allow memory to be retained(Reference McGaugh97). The process by which these modifications occur is called synaptic plasticity and, although the mechanisms underlying this process during learning and memory are not completely understood, a growing body of research has provided important clues(Reference Lamprecht and LeDoux98, Reference Muller, Nikonenko and Jourdain99). Long-term potentiation (LTP) is a form of synaptic plasticity widely accepted as the mechanism by which memories are laid down and subsequently stored(Reference Malenka and Nicoll100, Reference Bliss and Collingridge101). LTP refers to a persistent increase in synaptic strength between neurons that typically occurs during learning(Reference Lynch, Rex and Gall102). The initiation of LTP occurs when there is a simultaneous activation of both pre- and postsynaptic neuronal cells, which creates an associative link between the neurons involved.

During LTP, a release of glutamate from the presynaptic neuron leads to the activation of N-methyl-d-aspartate receptors in the postsynaptic cell, allowing an influx of Ca2+(Reference Kandel and Squire75, Reference Kandel103) (Fig. 2(Ai)). When the intracellular levels of Ca2+ are sufficiently elevated, it triggers the activation of signalling pathways, such as cAMP-dependent protein kinase A(Reference Arnsten, Ramos and Birnbaum104), protein kinase B (also known as Akt)(Reference van der Heide, Ramakers and Smidt105, Reference Kumar, Zhang and Swank106), protein kinase C (PKC)(Reference Alkon, Sun and Nelson107), Ca-calmodulin kinase(Reference Bach, Hawkins and Osman108, Reference Lisman, Schulman and Cline109) and extracellular-signal-regulated kinase (ERK)(Reference Sweatt110, Reference Sweatt111) (Fig. 2(B)). Phosphorylation of these kinases results in the modulation of synaptic efficacy, which typically involves activation of α-amino-3-hydroxy-5-methyllisoxazole-4-propionic acid receptors(Reference Esteban, Shi and Wilson112, Reference Kim, Dunah and Wang113) and consequent modification of the biophysical properties of this receptor(Reference Malinow and Malenka114, Reference Zhu, Qin and Zhao115). For example, the activation of ERK1/2 by phosphorylation results in its translocation to the nucleus which triggers the novo gene expression and protein synthesis, a process that is crucial to maintain LTP and convert short-term memories into a more stable long-term form(Reference Kelleher, Govindarajan and Jung116, Reference Bozon, Kelly and Josselyn117) (Fig. 2(Aii)).

Fig. 2. (A) Molecular mechanisms underlying synaptic plasticity processes. (i) Activity-dependent release from presynaptic neurons lead to activation of α-amino-3-hydroxy-5-methyllisoxazole-4-propionic acid receptors (AMPAR) that causes depolarisation of the postsynaptic neuron, resulting in activation of N-methyl-d-aspartate receptors (NMDAR) and Ca2+ influx. (ii) Ca influx causes activation of kinase signalling pathways, which induces activation of transcription factors and induces gene expression and new protein synthesis. (iii) This leads to stabilisation of synaptic changes and contributes to morphological changes at the synapse through regulation of the cytoskeleton which will ultimately impact on learning and retention of memories. (B) Signalling pathways involved in controlling memory and learning in the hippocampus. Activation of signalling pathways such as protein kinase A (PKA), protein kinase C (PKC ), protein kinase B (also known as Akt); extracellular-signal-regulated kinase 1/2 (ERK1/2) and Ca-calmodulin kinase (CamK) converge to activate the transcription factor cAMP response element-binding protein (CREB) that regulates the transcription of many genes associated with synapse re-modelling, synaptic plasticity and memory. PSA-NCAM, polysialylated-neural cell adhesion molecule; TrkB, truncated tyrosin kinase B receptor; BDNF, brain-derived neurotrophic factor.

The persistence of memory depends on structural and morphological changes in neuronal connections, a process primarily mediated by new protein synthesis (Fig. 2(Aiii)). In fact, there is extensive evidence from several different species that long-term memory requires the transcription and translation of new proteins in order to be retained(Reference Davis and Squire118, Reference Goelet, Castellucci and Schacher119). In particular, the mammalian target of rapamycin, an Akt pathway target, plays a central role in translational control and has been shown to be critical for long-lasting plasticity(Reference Hoeffer and Klann120Reference Hou and Klann122). Most importantly, extensive evidence derived from experimental systems ranging from molluscs to human subjects indicates that the cAMP response element binding protein (CREB) is a core component of the molecular switch that converts short- to long-term memory(Reference Brightwell, Smith and Neve123Reference Barco, Pittenger and Kandel125). In mammals, CREB has been shown to regulate the expression of several genes during learning and memory, particularly gene products that are needed to stabilise the synaptic changes that are triggered during learning(Reference Bozon, Kelly and Josselyn117, Reference Impey, McCorkle and Cha-Molstad126, Reference Impey, Smith and Obrietan127) (Fig. 2(B)). The current list of target genes includes neurotrophins, proteins that influence cell signalling, cell structure and cell metabolism and other transcription factors, such as c-fos whose induction may trigger a second wave of changes in gene expression(Reference Leil, Ossadtchi and Nichols128Reference Lonze and Ginty130) (Fig. 2(B)).

Neurotrophins are critical molecules that support the development, differentiation, maintenance and plasticity of brain function(Reference McAllister, Katz and Lo131, Reference Poo132). Among these molecules, brain-derived neurotrophic factor (BDNF) is involved in translating neuronal signals into structural changes in the synapse(Reference Cohen-Cory and Fraser133Reference Thomas and Davies135). As such BDNF has been shown to be necessary to induce long-lasting structural changes at dendritic spines located at the terminals of excitatory synapses(Reference Bailey and Kandel136, Reference Tanaka, Horiike and Matsuzaki137). There is a considerable body of evidence suggesting that modulation of spine morphology correlates with synaptic plasticity and memory formation(Reference Bailey and Kandel136, Reference Nimchinsky, Sabatini and Svoboda138). Specifically, the increase in α-amino-3-hydroxy-5-methyllisoxazole-4-propionic acid receptors density at the synapse is thought to have a stabilising effect on spine morphology(Reference Fischer, Kaech and Wagner139) (Fig. 2(Aiii)). For example, the activity-regulated cytoskeletal-associated protein (Arc/Arg3.1), whose expression is known to be dependent on Akt–mammalian target of rapamycin activation, was found to regulate α-amino-3-hydroxy-5-methyllisoxazole-4-propionic acid receptor trafficking(Reference Kandel103). In agreement with this, the expression of Arc/Arg3.1 was shown to facilitate changes in synaptic strength and the induction of morphological changes, such as those dependent on actin-polymerisation(Reference Messaoudi, Kanhema and Soule140, Reference Tzingounis and Nicoll141) (Fig. 2(B)).

In addition to this, cell adhesion molecules have been shown to play important roles in synaptic plasticity processes during memory formation(Reference Bonfanti142). These molecules mediate the adhesion between cells, facilitating changes in synaptic connectivity. In particular, the neural cell adhesion molecule (NCAM) and its polysialated form, PSA NCAM, have been shown to regulate neurite outgrowth during memory formation, by mediating neuronal cell adhesion and signal transduction(Reference Dityatev, Dityateva and Sytnyk143Reference Kiss, Troncoso and Djebbara145). Overall, the stabilisation of connections between neuronal cells seems to be dependent on glutamate signalling that regulates and coordinates simultaneously both cytoskeletal and adhesion remodelling(Reference Lamprecht and LeDoux98) (Fig. 2).

On the whole, the formation of a memory involves several phases, including acquisition, during which molecular changes are initiated in specific synapses, and consolidation, when those cellular modifications become stabilised allowing the memory to be retained. Typically the circuits linking dentate gyrus to Cornu Ammonis 3 (CA3) are more involved with the encoding of the spatial information, while CA3–CA1 are related to consolidation and recalling of the information. The resulting modified neuronal circuit underlies the neural representation of memory in the brain.

The impact of flavonoid-rich foods on memory and learning

Animal investigations have clearly indicated that flavonoid-rich foods such as spinach, strawberry, blueberry, GB and green tea are beneficial in retarding and/or counteracting functional age-related cognitive deficits(Reference Cohen-Salmon, Venault and Martin19, Reference Williams, El Mohsen and Vauzour24, Reference Casadesus, Shukitt-Hale and Stellwagen25, Reference Joseph, Shukitt-Hale and Denisova27, Reference Li, Zhao and Zhang146, Reference Winter147). Historically, these diets were thought to be protective due to their antioxidant activity(Reference Rice-Evans, Miller and Paganga35, Reference Rice-Evans148); however, it has become clear that antioxidant capacity alone is not responsible for the ability of flavonoids-rich diets to prevent or reverse age-related neuronal and cognitive changes(Reference Joseph, Shukitt-Hale and Denisova27, Reference Spencer30, Reference Williams, Spencer and Rice-Evans149). Although the mechanisms by which flavonoids act in the brain remain a source of debate, a substantial number of flavonoid supplementation studies in animal models has provided important clues to their function. Investigations have pointed to many potential mechanisms, including the regulation of oxidative stress signals such as NF-κB(Reference Goyarzu, Malin and Lau150), enhancement of neuroprotective stress shock proteins(Reference Galli, Bielinski and Szprengiel151) and anti-inflammatory actions through the regulation of the expression of specific inflammatory genes (IL-1β, TNFα)(Reference Shukitt-Hale, Lau and Carey152). In the following sections, we will focus on the potential of flavonoids to modulate and influence the molecular architecture responsible for learning and memory in the brain and how such activity may underpin behavioural changes induced by flavonoid-rich diets and pure compounds.

Green tea

There are an extensive number of studies regarding neuroprotection induced by green tea flavonoids in cellular and animal models, suggesting a potential therapeutic use of these compounds in regenerating injured neuronal cells(Reference Mandel and Youdim29, Reference Mandel, Amit and Kalfon153, Reference Mandel, Avramovich-Tirosh and Reznichenko154). Green tea contains a high amount of flavanols (also referred to as catechins), which constitute 30–45% of the solid green tea extract(Reference Khokhar and Magnusdottir155, Reference Higdon and Frei156). The most abundant polyphenolic compound is (−)-EGC-3-gallate, followed by (−) EGC, EC and (−)-EC-3-gallate (Table 1)(Reference Graham157). Human epidemiological and animal data suggest that tea may decrease the incidence of dementia, Alzheimer's disease (AD) and Parkinson's disease(Reference Kuriyama, Hozawa and Ohmori14, Reference Kim, Kim and Kim158, Reference Hu, Bidel and Jousilahti159). In support of this, recent animal studies have shown that green tea intake helps to prevent age-related cognitive deficits (Table 2), particularly after long-term administration of green tea (approximately 6 months), which was shown to positively influence memory and learning in both normally aged and senescence-accelerated animals(Reference Li, Zhao and Zhang96, Reference Li, Zhao and Zhang146, Reference Assuncao, Santos-Marques and Carvalho160).

Table 2. Effects of flavonoid-rich foods (Gingko biloba, green tea and blueberries) on memory and learning in rodents

BW, body weight; MWM, Morris Water Maze; LTP, long-term potentiation; RAM, radial arm maze; CREB, cAMP response element binding protein; 5-HT, serotonin; AChE, acetylcholinesterase; ROS, reactive oxygen species; CaMKII, Ca2+/calmodulin–dependent protein kinase II; BDNF, brain-derived neurotrophic factor; PSD95, postsynaptic density protein-95; Bcl-2, B–cell lymphocytic–leukaemia proto–oncogene 2; PKA, protein kinase A; ERK, extracellular–signal–regulated kinase; IGF-1, insulin-like growth factor 1; IGF-1R, IGF-1 receptor; NMDAR, N-methyl-d-aspartate receptor; NR2B, N-methyl-d-aspartate receptor sub-type 2B; mTOR, mammalian target of rapamycin; GAP 43, growth associated protein 43; PhPKC, neutral sphingomyelin-specific phospholipase C.

Tea flavonoids have been reported to be potent Fe chelators, radical scavenging agents and to have anti-inflammatory activities(Reference Nanjo, Goto and Seto161Reference Weinreb, Amit and Youdim166). In addition to these effects, recent studies have also indicated that they are capable of modulating signal transduction pathways and of regulating gene expression, and that these effects may also contribute to the neuroprotective effects of these compounds(Reference Mandel and Youdim29, Reference Mandel, Amit and Weinreb167). For example, in vitro and in vivo studies suggest an ability of green tea catechins to regulate apoptotic pathways(Reference Choi, Jung and Lee168, Reference Mandel, Maor and Youdim169) as well as cell survival-related kinase signalling pathways, such as mitogen-activated protein kinase(Reference Chen, Yu and Owuor170), PKC(Reference Levites, Amit and Youdim171) and phosphoinositide 3–kinase–Akt(Reference Koh, Kim and Kwon172). A great deal of research has been devoted to the ability of green tea catechins, especially EGC-3-gallate, to activate the PKC pathway(Reference Levites, Amit and Youdim171, Reference Levites, Amit and Mandel173, Reference Kalfon, Youdim and Mandel174). Notably, a 2-week pretreatment with a green tea catechin (EGC-3-gallate) was shown to be protective against Aβ-induced neurotoxicity by attenuating the depletion of PKC isoforms in the hippocampus and decreasing amyloid precursor protein(Reference Levites, Amit and Mandel173). The PKC family has a fundamental role in the regulation of cell survival(Reference Maher175, Reference Dempsey, Newton and Mochly-Rosen176), LTP and memory consolidation(Reference Sun, Hongpaisan and Alkon177Reference Sun and Alkon179).

In agreement with these molecular findings, the long-term administration of green tea flavanols has been shown to prevent spatial memory and learning impairments in a senescence-accelerated mouse model (senescence-accelerated mouse prone-8), which was paralleled by the activation of the protein kinase A–CREB pathway(Reference Li, Zhao and Zhang96). Furthermore, green tea flavanol intake prevented reductions in the levels of key proteins involved in synaptic plasticity and structural plasticity, such as BDNF, postsynaptic density protein-95 and Ca2+/calmodulin-dependent protein kinase II(Reference Li, Zhao and Zhang96) (Table 2). In support of this, another study using healthy, aged animals highlighted similar beneficial effects of green tea flavanols (6-month intervention) on spatial memory, along with increased levels of hippocampal CREB phosphorylation and increased levels of some of its target genes, such as BDNF and Bcl-2(Reference Li, Zhao and Zhang146). These studies indicate that green tea flavanols may prevent memory decline by regulating crucial synaptic-related proteins in the hippocampus, potentially via the CREB pathway. The literature regarding the potential beneficial effects of green tea in young healthy subjects is limited, although there is some evidence of a significant (P<0·0002) improvement in working and reference memory of young rats (1-month-old) in Radial Arm Maze following a 6-month oral administration(Reference Haque, Hashimoto and Katakura12) (Table 2).

Blueberry and other berries

There have been many studies reporting the potential effects of berry supplementation on spatial memory in aged animals(Reference Joseph, Shukitt-Hale and Denisova27, Reference Joseph, Shukitt-Hale and Denisova180Reference Shukitt-Hale, Cheng and Bielinski183). Early studies indicated that long-term supplementation (from 6 to 15 months of age) with berries (blueberry or strawberry) retards age-related decrements in cognitive and neuronal function(Reference Joseph, Shukitt-Hale and Denisova181). In subsequent experiments, supplementation with strawberry or blueberry reversed age-related deficits in spatial memory in aged rats(Reference Joseph, Shukitt-Hale and Denisova27) and a 2% blackberry-supplemented diet is effective in reversing age-related deficits in motor performance and spatial memory (MWM) when fed to aged rats (19-month-old) for 8 weeks(Reference Shukitt-Hale, Cheng and Joseph182). However, among berry fruits, blueberries have proved most effective at improving spatial learning and memory in old animals. Blueberries contain high levels of a variety of anthocyanins, such as malvidin, delphinidin, petunidin, peonidin and cyanidin(Reference Borges, Degeneve and Mullen184), which could explain the particular beneficial effects of blueberries compared with other berries(Reference Shukitt-Hale, Galli and Meterko185). However, blueberries also contain significant amounts of flavanols, flavonols and other phenolics, such as (−)-EC, (+)-catechin and quercetin (Table 1)(Reference Harnly, Doherty and Beecher34), which may play a role in defining their beneficial effects. Furthermore, blueberry appears to have a more pronounced effect on short-term memory than on long-term memory, as demonstrated by an improved performance in several memory maze tasks, such as the MWM, eight-arm Radial Arm Maze and an X-maze(Reference Williams, El Mohsen and Vauzour24, Reference Joseph, Shukitt-Hale and Denisova27, Reference Ramirez, Izquierdo and do Carmo Bassols Raseira186) (Table 2).

In addition to healthy, aged rodent models, blueberry supplementation has also been shown to have a positive impact on neuronal function and memory in rodent models of accelerated aging(Reference Shukitt-Hale, Carey and Jenkins187). These models are characterised by enhanced indices of oxidative stress and inflammation along with disruption of the dopaminergic system, similar to that observed in healthy, aged animals(Reference Shukitt-Hale, Carey and Jenkins187). Furthermore, a blueberry-rich diet was also shown to be protective in AD models (amyloid precursor protein/PS1 transgenic mice), preventing spatial memory deficits along with enhancement of memory-associated neuronal signalling(Reference Joseph, Denisova and Arendash180). In particular, blueberry-supplemented amyloid precursor protein/PS1 mice exhibited greater levels of hippocampal ERK activation as well as hippocampal PKCα activation, both known to be involved in regulation of synaptic plasticity and consolidation of learning and memory(Reference Joseph, Denisova and Arendash180). In agreement with this, blueberry-supplementation (2% w/w) in aged animals has been shown to regulate important markers of synaptic and structural plasticity, notably ERK–CREB–BDNF and Akt–mammalian target of rapamycin–Arc pathways along with improvement in spatial learning in the X-maze within 3 weeks of supplementation(Reference Williams, El Mohsen and Vauzour24) (Table 2). These pathways are dependent on N-methyl-d-aspartate receptor activation and play a crucial role in gene expression and de novo protein synthesis(Reference Davis and Squire118). In support of this, a 6–8-week supplementation with a blueberry extract resulted in improved N-methyl-d-aspartate receptor-dependent LTP in aged animals(Reference Coultrap, Bickford and Browning188) (Table 2). Ultimately, these molecular mechanisms underlie the typical morphological changes that occur at the neuronal level during learning processes, although regulation at this structural level has not been investigated following blueberry supplementation.

On the other hand, increased ERK and insulin-like growth factor 1 activation has been observed in the dentate gyrus of blueberry-fed older animals and these cellular events were associated with increased neurogenesis (proliferation of precursor cells) and enhanced spatial memory(Reference Casadesus, Shukitt-Hale and Stellwagen25) (Table 2). The link between dentate gyrus neurogenesis, cognitive performance and aging is well documented with increasing evidence showing that an increase in neurogenesis is associated with improved cognition(Reference Drapeau, Mayo and Aurousseau189Reference Shors, Townsend and Zhao195). Physical exercise, for instance, is described as one of the strongest neurogenic stimuli(Reference van Praag196). Likewise, neurogenesis may represent one mechanism by which blueberry flavonoids improve memory by acting on the hippocampus. Overall, there is strong evidence suggesting that blueberry can improve memory and learning in aged animals and that these improvements are linked to the modulation of important structural and synaptic plasticity markers.

Ginkgo biloba

Standardised extracts of GB leaves have been extensively investigated for their potential to enhance memory and cognitive function. These extracts consist of numerous components, including flavonols (about 30%) and terpenelactones (7%), which are regarded as being responsible for the observed neuroprotective properties of GB(Reference DeFeudis and Drieu197). Several human interventions have reported beneficial effects of GB in the prevention and treatment of neurodegenerative disorders, such as AD, in particular, enhancement of cognitive function(Reference Le Bars, Katz and Berman198Reference Kanowski and Hoerr200), memory(Reference Kanowski, Herrmann and Stephan201) and concentration(Reference Chan, Xia and Fu202, Reference Le Bars, Velasco and Ferguson203). Meta-analyses have also revealed significant beneficial effects of GB extract with regard to the treatment of dementia and cognitive functions associated with AD(Reference Hoerr199, Reference Kanowski, Herrmann and Stephan201, Reference Oken, Storzbach and Kaye204). For instance, a significant effect was found (3% difference in the AD Assessment Scale-cognitive subtest) after a 3–6-month treatment with 120–240 mg GB extract on objective measures of cognitive function in AD(Reference Oken, Storzbach and Kaye204, Reference Sierpina, Wollschlaeger and Blumenthal205).

Early studies in rodents showed that chronic supplementation with GB extract resulted in substantial improvements in learning and memory in aged rodents(Reference Cohen-Salmon, Venault and Martin19, Reference Winter147, Reference Winter206, Reference Topic, Hasenohrl and Hacker207) (Table 2). Overall, chronic supplementation with GB seems to improve spatial learning in a number of different tasks, namely MWM, T-Maze and Radial Arm Maze. Although most studies seem to show a greater effect in aged and/or cognitively impaired animals, there are some studies showing positive effects on cognitive performance in young rodents(Reference Oliveira, Sanada and Saragossa Filho17, Reference Shif, Gillette and Damkaoutis18, Reference Hoffman, Donato and Robbins208, Reference Walesiuk, Trofimiuk and Braszko209) (Table 2). While the mechanisms underlying the neuroprotective actions of GB are unclear, there is some evidence showing that GB extract can regulate the levels of neurotransmitters, such as serotonin(Reference Blecharz-Klin, Piechal and Joniec210), influence neurotransmitter receptors(Reference Huang, Duke and Chebib211Reference Ivic, Sands and Fishkin213), regulate structural changes in hippocampal circuitry(Reference Cohen-Salmon, Venault and Martin19), affect neuronal excitability(Reference Williams, Watanabe and Schultz214) and trigger neurogenesis in the hippocampus(Reference Tchantchou, Xu and Wu215). In addition, GB-supplemented mice show an up-regulation of several neuromodulatory elements, such as α-amino-3-hydroxy-5-methyllisoxazole-4-propionic acid-type glutamate receptors and microtubule-associated Tau(Reference Watanabe, Wolffram and Ader216). These data suggest a link between GB-induced improvements in memory and modulation of different aspects of synaptic plasticity. In support of this, 1 month of GB supplementation has been observed to increase the magnitude of LTP recorded in the hippocampal CA1 area of aged rats leading to an enhancement of spatial learning in MWM(Reference Wang, Wang and Wu217). More recently, 7 d intervention with GB in young animals has been observed to regulate hippocampal expression of the transcription factor CREB(Reference Oliveira, Sanada and Saragossa Filho17).

Pure flavonoids

At present, the majority of the studies investigating the impact of flavonoids on memory, learning and cognition involve the supplementation of whole foods and beverages, rich in a complex array of macro- and micronutrients as well as a diverse range of different flavonoids. As such, causal relationships between individual flavonoids and function are difficult to establish. To address this, studies investigating the effects of individual flavonoids are beginning to emerge (Table 3). For example, the flavanol fisetin, typically found in strawberries, has been shown to enhance recognition memory in mice(Reference Maher, Akaishi and Abe218), through the activation of ERK and induction of CREB phosphorylation as well as a facilitation of LTP(Reference Maher, Akaishi and Abe218). Although the effect of fisetin on memory was assessed after oral supplementation in vivo, the approach used ex vivo to investigate the underlying mechanisms(Reference Maher, Akaishi and Abe218) limits the interpretation of the data since it excludes crucial factors that may affect the bioactivity of the compound, such as absorption and metabolism.

Table 3. Effects of pure flavonoids on memory and learning in rodents

ERK, extracellular-signal-regulated kinase; CREB, cAMP response element binding protein; LTP, long-term potentiation; RAM, radial arm maze; MWM, Morris water maze; DG, dentate gyrus; BDNF, brain-derived neurotrophic factor.

The flavanol (−)-EC (found in cocoa, blueberry and green tea) has been shown to improve the retention of spatial memory in the MWM when administered in its pure form. In the paradigms used in these studies, the effects of (−)-EC were enhanced when combined with exercise(Reference van Praag, Lucero and Yeo70) and improvements in memory appeared to be associated with increased angiogenesis and neuronal spine density in the dentate gyrus of the hippocampus along with up-regulation of genes associated with learning(Reference van Praag, Lucero and Yeo70). Oral administration of fustin, a flavonoid found in GB, has been shown to attenuate β-amyloid induced learning impairments(Reference Jin, Shin and Park219), in a comparable way to that observed for EGb 761, a standard extract of GB. In agreement with data for other flavonoid-rich foods, the ERK–CREB–BDNF pathway was shown to be important for the M1 receptor-mediated cognition enhancing effects of fustin(Reference Jin, Shin and Park219).

Although data are currently limited, pure flavonoids do appear to be able to induce learning and memory performance in a similar manner to flavonoid-rich foods and/or beverages. There is also evidence that pure flavonoids, such as (−)-EC and fisetin, are able to modulate molecular pathways necessary for memory and learning(Reference Maher220, Reference Schroeter, Bahia and Spencer221). For example, pure (−)-EC induces both ERK1/2 and CREB activation in cortical neurons and subsequently increases CREB-regulated gene expression(Reference Schroeter, Bahia and Spencer221), while nanomolar concentrations of pure quercetin are effective at enhancing CREB activation(Reference Spencer, Rice-Evans and Williams222). Such evidence suggests that it is the flavonoids within these foods and beverages that mediate changes in memory formation in vivo.

Summary and future perspectives

Flavonoid-rich foods such as green tea and berries appear to be capable of influencing memory and learning through an ability of the flavonoids they contain to modulate and enhance cellular events that underlie memory formation in the hippocampus. Most notably, flavonoids have been shown to affect different aspects of synaptic plasticity, from regulation of receptors activation(Reference Coultrap, Bickford and Browning188), modulation of signalling pathways(Reference Williams, El Mohsen and Vauzour24), activation of transcription factors(Reference Li, Zhao and Zhang96, Reference Li, Zhao and Zhang146), regulation of gene expression and protein expression(Reference Weinreb, Amit and Youdim166, Reference Weinreb, Amit and Youdim223), modulation of morphological and structural aspects of neurons(Reference van Praag, Lucero and Yeo70) and promotion of LTP(Reference Maher, Akaishi and Abe218). Although many distinct signalling pathways are known to be involved in learning and memory formation, flavonoid interventions seem to interact primarily with ERK and Akt pathways, leading to modulation of the transcription factor CREB(Reference Williams, El Mohsen and Vauzour24, Reference Li, Zhao and Zhang96, Reference Li, Zhao and Zhang146) as well as up-regulation of CREB gene expression(Reference Oliveira, Sanada and Saragossa Filho17).

The data to date suggest that CREB may be a crucial target for flavonoids. In this respect, there has been an interest in developing drugs that target CREB leading to enhancements in memory and learning(Reference Tully, Bourtchouladze and Scott224). Furthermore, the ability of these compounds to modulate neurotrophic factors such as BDNF makes them useful targets for the prevention of cognitive decline since these are crucial for neuronal survival and for the protection of neurons from injury(Reference Radecki, Brown and Martinez225). BDNF levels are known to decline during aging and their levels have been shown to correlate with human learning and memory(Reference Garzon, Yu and Fahnestock226Reference Laske, Stransky and Leyhe229), which has driven a considerable amount of research into design drugs that target BDNF and regulate its endogenous levels in the brain(Reference Fumagalli, Racagni and Riva230). Indeed, drugs used to prevent AD such as memantine, as well as newly developed therapeutic interventions, both target BDNF and its levels in brain regions affected by the disease(Reference Marvanova, Lakso and Pirhonen231Reference Mackowiak, O'Neill and Hicks233). As such, further investigation into the impact of flavonoids and flavonoid-rich foods on levels of neurotrophins such as BDNF, is worthy of investigation. Allied to this, a more detailed examination of how flavonoids impact on BDNF levels in specific regions of the hippocampus when combined with highly specific behavioural tasks that engage preferentially specific areas of the hippocampus may help shed additional light on the underlying mechanisms of the action of flavonoids on different aspects of the learning process.

Future studies should also consider supplementation with pure flavonoids. A considerable level of complexity exists in interpreting this type of experimental data, stemming from the fact that the majority of dietary supplementation studies use complex mixtures of ingredients (foods or beverages). The identification of specific active molecules responsible for the claimed benefits or potentially synergetic effects of different compounds can help to shed light on the mechanisms by which flavonoids act in the brain and inform future human studies. The identification of the active components in foods and beverages is also a crucial step to establish a causal relationship between flavonoid intake and improvements in memory and learning measures. This should be paralleled with inhibitor studies to investigate whether pathway inhibition (e.g. ERK–CREB–BDNF) effectively blocks changes in spatial memory observed in flavonoid-supplemented animals. Furthermore, studies are required to establish the impact of flavonoids on structural aspects of synaptic plasticity such as synapse growth and dendritic spine density, events that are modulated by the aforementioned pathways. Recent data showing that flavonoids can impact on aspects of neuronal structure and morphology, such as spine density are highly promising(Reference van Praag, Lucero and Yeo70). In particular, further investigation into whether these structural changes are specific to distinct regions of the hippocampus will be valuable given that it is well reported that aging leads to region- and circuit-specific losses of connectivity in the hippocampus(Reference Wilson, Ikonen and Gallagher95, Reference Burke and Barnes234, Reference Gallagher235).

Since aging affects different aspects of synaptic plasticity, from activation of signalling pathways to structural changes neurons, it is not surprising that flavonoids, which also impact on these different levels of functioning, may help ameliorate age-related memory and learning impairments. However, there have been relatively few investigations into the potential of flavonoid-rich diets to improve memory and learning in young animals. Future investigations are warranted to fully explore the impact of flavonoids on young animal and to explore whether common mechanism of activity exist in both young and aged animals. Such studies will inform the design of future experiments required to address the temporal nature of these effects over the lifetime of an animal and clarify whether consumption of flavonoid-rich foods delays the onset of age-related cognitive impairments.

Overall, there is strong evidence that flavonoid-rich foods can impact on memory and learning and that this seems likely to involve, to some degree, regulation of signalling cascades, leading to changes in morphological aspects of neuronal cells, such as spine density, that ultimately impact on synaptic plasticity and more sustained LTP in the hippocampus. Future work should focus on investigating further these mechanisms in order to establish causal relationships between flavonoid intake, cognitive outputs and modulation of synaptic plasticity markers.

Acknowledgements

This research was supported by the Biotechnology and Biological Sciences Research Council (grant no. BB/F008953/1) and is greatly appreciated. The authors declare no conflict of interest. C. R., J. P. E. S., J. D. T. G. and C. M. W. all helped draft the manuscript.

References

1.Parrott, MD & Greenwood, CE (2007) Dietary influences on cognitive function with aging: from high-fat diets to healthful eating. Ann N Y Acad Sci 1114, 389397.Google Scholar
2.Gomez-Pinilla, F (2008) Brain foods: the effects of nutrients on brain function. Nat Rev Neurosci 9, 568578.Google Scholar
3.Greenwood, CE & Winocur, G (2005) High-fat diets, insulin resistance and declining cognitive function. Neurobiol Aging 26, Suppl. 1, 4245.CrossRefGoogle ScholarPubMed
4.Molteni, R, Barnard, RJ, Ying, Z et al. (2002) A high-fat, refined sugar diet reduces hippocampal brain-derived neurotrophic factor, neuronal plasticity, and learning. Neuroscience 112, 803814.Google Scholar
5.Ingram, DK, Weindruch, R, Spangler, EL et al. (1987) Dietary restriction benefits learning and motor performance of aged mice. J Gerontol 42, 7881.Google Scholar
6.Johnson, JB, Summer, W, Cutler, RG et al. (2007) Alternate day calorie restriction improves clinical findings and reduces markers of oxidative stress and inflammation in overweight adults with moderate asthma. Free Radic Biol Med 42, 665674.Google Scholar
7.Letenneur, L, Proust-Lima, C, Le Gouge, A et al. (2007) Flavonoid intake and cognitive decline over a 10-year period. Am J Epidemiol 165, 13641371.CrossRefGoogle ScholarPubMed
8.Patel, AK, Rogers, JT & Huang, X (2008) Flavanols, mild cognitive impairment, and Alzheimer's dementia. Int J Clin Exp Med 1, 181191.Google Scholar
9.Beking, K & Vieira, A (2011) Flavonoid intake and disability-adjusted life years due to Alzheimer's and related dementias: a population-based study involving twenty-three developed countries. Public Health Nutr 13, 14031409.Google Scholar
10.Nurk, E, Refsum, H, Drevon, CA et al. (2009) Intake of flavonoid-rich wine, tea, and chocolate by elderly men and women is associated with better cognitive test performance. J Nutr 139, 120127.Google Scholar
11.Chan, YC, Hosoda, K, Tsai, CJ et al. (2006) Favorable effects of tea on reducing the cognitive deficits and brain morphological changes in senescence-accelerated mice. J Nutr Sci Vitaminol (Tokyo) 52, 266273.Google Scholar
12.Haque, AM, Hashimoto, M, Katakura, M et al. (2006) Long-term administration of green tea catechins improves spatial cognition learning ability in rats. J Nutr 136, 10431047.CrossRefGoogle ScholarPubMed
13.Kaur, T, Pathak, CM, Pandhi, P et al. (2008) Effects of green tea extract on learning, memory, behavior and acetylcholinesterase activity in young and old male rats. Brain Cogn 67, 2530.Google Scholar
14.Kuriyama, S, Hozawa, A, Ohmori, K et al. (2006) Green tea consumption and cognitive function: a cross-sectional study from the Tsurugaya Project 1. Am J Clin Nutr 83, 355361.CrossRefGoogle ScholarPubMed
15.Lai, HC, Chao, WT, Chen, YT et al. (2004) Effect of EGCG, a major component of green tea, on the expression of Ets-1, c-Fos, and c-Jun during angiogenesis in vitro. Cancer Lett 213, 181188.Google Scholar
16.Unno, K, Takabayashi, F, Yoshida, H et al. (2007) Daily consumption of green tea catechin delays memory regression in aged mice. Biogerontology 8, 8995.Google Scholar
17.Oliveira, DR, Sanada, PF, Saragossa Filho, AC et al. (2009) Neuromodulatory property of standardized extract Ginkgo biloba L. (EGb 761) on memory: behavioral and molecular evidence. Brain Res 1269, 6889.CrossRefGoogle ScholarPubMed
18.Shif, O, Gillette, K, Damkaoutis, CM et al. (2006) Effects of Ginkgo biloba administered after spatial learning on water maze and radial arm maze performance in young adult rats. Pharmacol Biochem Behav 84, 1725.Google Scholar
19.Cohen-Salmon, C, Venault, P, Martin, B et al. (1997) Effects of Ginkgo biloba extract (EGb 761) on learning and possible actions on aging. J Physiol Paris 91, 291300.Google Scholar
20.Itil, TM, Eralp, E, Ahmed, I et al. (1998) The pharmacological effects of Gingko Biloba, a plant extract, on the brain of dementia patients in comparison with tacrine. Psychopharmacology 34, 391396.Google ScholarPubMed
21.Fisher, ND, Sorond, FA & Hollenberg, NK (2006) Cocoa flavanols and brain perfusion. J Cardiovasc Pharmacol 47, Suppl. 2, S210S214.Google Scholar
22.Francis, ST, Head, K, Morris, PG et al. (2006) The effect of flavanol-rich cocoa on the fMRI response to a cognitive task in healthy young people. J Cardiovasc Pharmacol 47, Suppl. 2, S215S220.CrossRefGoogle ScholarPubMed
23.Dinges, DF (2006) Cocoa flavanols, cerebral blood flow, cognition, and health: going forward. J Cardiovasc Pharmacol 47, Suppl. 2, S221S223.CrossRefGoogle ScholarPubMed
24.Williams, CM, El Mohsen, MA, Vauzour, D et al. (2008) Blueberry-induced changes in spatial working memory correlate with changes in hippocampal CREB phosphorylation and brain-derived neurotrophic factor (BDNF) levels. Free Radic Biol Med 45, 295305.Google Scholar
25.Casadesus, G, Shukitt-Hale, B, Stellwagen, HM et al. (2004) Modulation of hippocampal plasticity and cognitive behavior by short-term blueberry supplementation in aged rats. Nutr Neurosci 7, 309316.Google Scholar
26.Shukitt-Hale, B, Lau, FC & Joseph, JA (2008) Berry fruit supplementation and the aging brain. J Agric Food Chem 56, 636641.Google Scholar
27.Joseph, JA, Shukitt-Hale, B, Denisova, NA et al. (1999) Reversals of age-related declines in neuronal signal transduction, cognitive, and motor behavioral deficits with blueberry, spinach, or strawberry dietary supplementation. J Neurosci 19, 81148121.Google Scholar
28.Krikorian, R, Shidler, MD, Nash, TA et al. (2010) Blueberry supplementation improves memory in older adults. J Agric Food Chem 58, 39964000.Google Scholar
29.Mandel, S & Youdim, MB (2004) Catechin polyphenols: neurodegeneration and neuroprotection in neurodegenerative diseases. Free Radic Biol Med 37, 304317.CrossRefGoogle ScholarPubMed
30.Spencer, JP (2007) The interactions of flavonoids within neuronal signalling pathways. Genes Nutr 2, 257273.Google Scholar
31.Spencer, JP (2008) Flavonoids: modulators of brain function? Br J Nutr 99E, Suppl. 1, ES60ES77.Google Scholar
32.Shukitt-Hale, B, Carey, A & Joseph, JA (2005) Phytochemicals in foods and beverages: effects on the central nervous system. In Nutritional Neuroscience, pp. 393403 [Prasad, C]. Boca Raton: CRC Press.Google Scholar
33.Beking, K & Vieira, A (2011) An assessment of dietary flavonoid intake in the UK and Ireland. Int J Food Sci Nutr 62, 1719.Google Scholar
34.Harnly, JM, Doherty, RF, Beecher, GR et al. (2006) Flavonoid content of U.S. fruits, vegetables, and nuts. J Agric Food Chem 54, 99669977.Google Scholar
35.Rice-Evans, CA, Miller, NJ & Paganga, G (1996) Structure-antioxidant activity relationships of flavonoids and phenolic acids. Free Radic Biol Med 20, 933956.Google Scholar
36.Scalbert, A & Williamson, G (2000) Dietary intake and bioavailability of polyphenols. J Nutr 130, 8S Suppl., 2073S2085S.Google Scholar
37.Manach, C, Scalbert, A, Morand, C et al. (2004) Polyphenols: food sources and bioavailability. Am J Clin Nutr 79, 727747.Google Scholar
38.Scalbert, A, Morand, C, Manach, C et al. (2002) Absorption and metabolism of polyphenols in the gut and impact on health. Biomed Pharmacother 56, 276282.Google Scholar
39.Spencer, JP, Chowrimootoo, G, Choudhury, R et al. (1999) The small intestine can both absorb and glucuronidate luminal flavonoids. FEBS Lett 458, 224230.Google Scholar
40.Crozier, A, Jaganath, IB & Clifford, MN (2009) Dietary phenolics: chemistry, bioavailability and effects on health. Nat Prod Rep 26, 10011043.Google Scholar
41.Spencer, JP (2003) Metabolism of tea flavonoids in the gastrointestinal tract. J Nutr 133, 3255S3261S.Google Scholar
42.Crozier, A, Del Rio, D & Clifford, MN (2010) Bioavailability of dietary flavonoids and phenolic compounds. Mol Aspects Med 31, 446467.Google Scholar
43.Stalmach, A, Mullen, W, Steiling, H et al. (2010) Absorption, metabolism, and excretion of green tea flavan-3-ols in humans with an ileostomy. Mol Nutr Food Res 54, 323334.Google Scholar
44.Renouf, M, Guy, P, Marmet, C et al. (2010) Plasma appearance and correlation between coffee and green tea metabolites in human subjects. Br J Nutr 104, 16351640.Google Scholar
45.Del Rio, D, Borges, G & Crozier, A (2010) Berry flavonoids and phenolics: bioavailability and evidence of protective effects. Br J Nutr 104, Suppl. 3, S67S90.Google Scholar
46.Kay, CD (2006) Aspects of anthocyanin absorption, metabolism and pharmacokinetics in humans. Nutr Res Rev 19, 137146.Google Scholar
47.Mazza, G, Kay, CD, Cottrell, T et al. (2002) Absorption of anthocyanins from blueberries and serum antioxidant status in human subjects. J Agric Food Chem 50, 77317737.Google Scholar
48.Wu, X, Cao, G & Prior, RL (2002) Absorption and metabolism of anthocyanins in elderly women after consumption of elderberry or blueberry. J Nutr 132, 18651871.Google ScholarPubMed
49.Borges, G, Roowi, S, Rouanet, JM et al. (2007) The bioavailability of raspberry anthocyanins and ellagitannins in rats. Mol Nutr Food Res 51, 714725.Google Scholar
50.Sakakibara, H, Ogawa, T, Koyanagi, A et al. (2009) Distribution and excretion of bilberry anthocyanins [corrected] in mice. J Agric Food Chem 57, 76817686.Google Scholar
51.Kay, CD, Kroon, PA & Cassidy, A (2009) The bioactivity of dietary anthocyanins is likely to be mediated by their degradation products. Mol Nutr Food Res 53, Suppl. 1, S92–S101.Google Scholar
52.Kahle, K, Kraus, M, Scheppach, W et al. (2006) Studies on apple and blueberry fruit constituents: do the polyphenols reach the colon after ingestion? Mol Nutr Food Res 50, 418423.Google Scholar
53.Spencer, JP, Abd El Mohsen, MM, Minihane, AM et al. (2008) Biomarkers of the intake of dietary polyphenols: strengths, limitations and application in nutrition research. Br J Nutr 99, 1222.Google Scholar
54.Aura, AM, Martin-Lopez, P, O'Leary, KA et al. (2005) In vitro metabolism of anthocyanins by human gut microflora. Eur J Nutr 44, 133142.Google Scholar
55.Tsuda, T, Horio, F & Osawa, T (1999) Absorption and metabolism of cyanidin 3-O-beta-d-glucoside in rats. FEBS Lett 449, 179182.Google Scholar
56.Vitaglione, P, Donnarumma, G, Napolitano, A et al. (2007) Protocatechuic acid is the major human metabolite of cyanidin-glucosides. J Nutr 137, 20432048.CrossRefGoogle ScholarPubMed
57.Williamson, G & Clifford, MN (2010) Colonic metabolites of berry polyphenols: the missing link to biological activity? Br J Nutr 104, Suppl. 3, S48S66.Google Scholar
58.Milbury, PE & Kalt, W (2010) Xenobiotic metabolism and berry flavonoid transport across the blood-brain barrier. J Agric Food Chem 58, 39503956.Google Scholar
59.Youdim, KA, Dobbie, MS, Kuhnle, G et al. (2003) Interaction between flavonoids and the blood-brain barrier: in vitro studies. J Neurochem 85, 180192.CrossRefGoogle ScholarPubMed
60.Aasmundstad, TA, Morland, J & Paulsen, RE (1995) Distribution of morphine 6-glucuronide and morphine across the blood-brain barrier in awake, freely moving rats investigated by in vivo microdialysis sampling. J Pharmacol Exp Ther 275, 435441.Google Scholar
61.Sperker, B, Backman, JT & Kroemer, HK (1997) The role of beta-glucuronidase in drug disposition and drug targeting in humans. Clin Pharmacokinet 33, 1831.CrossRefGoogle ScholarPubMed
62.Suganuma, M, Okabe, S, Oniyama, M et al. (1998) Wide distribution of [3H](−)-epigallocatechin gallate, a cancer preventive tea polyphenol, in mouse tissue. Carcinogenesis 19, 17711776.Google Scholar
63.Abd El Mohsen, MM, Kuhnle, G, Rechner, AR et al. (2002) Uptake and metabolism of epicatechin and its access to the brain after oral ingestion. Free Radic Biol Med 33, 16931702.Google Scholar
64.Talavera, S, Felgines, C, Texier, O et al. (2005) Anthocyanin metabolism in rats and their distribution to digestive area, kidney, and brain. J Agric Food Chem 53, 39023908.Google Scholar
65.El Mohsen, MA, Marks, J, Kuhnle, G et al. (2006) Absorption, tissue distribution and excretion of pelargonidin and its metabolites following oral administration to rats. Br J Nutr 95, 5158.Google Scholar
66.Peng, HW, Cheng, FC, Huang, YT et al. (1998) Determination of naringenin and its glucuronide conjugate in rat plasma and brain tissue by high-performance liquid chromatography. J Chromatogr B Biomed Sci Appl 714, 369374.Google Scholar
67.Andres-Lacueva, C, Shukitt-Hale, B, Galli, RL et al. (2005) Anthocyanins in aged blueberry-fed rats are found centrally and may enhance memory. Nutr Neurosci 8, 111120.Google Scholar
68.Kalt, W, Blumberg, JB, McDonald, JE et al. (2008) Identification of anthocyanins in the liver, eye, and brain of blueberry-fed pigs. J Agric Food Chem 56, 705712.Google Scholar
69.Passamonti, S, Vrhovsek, U, Vanzo, A et al. (2005) Fast access of some grape pigments to the brain. J Agric Food Chem 53, 70297034.Google Scholar
70.van Praag, H, Lucero, MJ, Yeo, GW et al. (2007) Plant-derived flavanol ( −)epicatechin enhances angiogenesis and retention of spatial memory in mice. J Neurosci 27, 58695878.Google Scholar
71.Squire, LR & Zola, SM (1996) Structure and function of declarative and nondeclarative memory systems. Proc Natl Acad Sci USA 93, 1351513522.Google Scholar
72.Squire, LR & Kandel, ER (2009) From Mind to Molecules, 2nd ed. Singapore: Ben Roberts.Google Scholar
73.Cohen, NJ & Eichenbaum, H (1993) Memory, Amnesia and the Hippocampal System. Cambridge, MA: MIT Press.Google Scholar
74.Lechner, HA, Squire, LR & Byrne, JH (1999) 100 years of consolidation – remembering Muller and Pilzecker. Learn Mem 6, 7787.Google Scholar
75.Kandel, ER & Squire, LR (2000) Memory: From Mind to Molecules. New York: W. H. Freeman.Google Scholar
76.Frankland, PW & Bontempi, B (2005) The organization of recent and remote memories. Nat Rev Neurosci 6, 119130.Google Scholar
77.Squire, LR, Stark, CEL & Clark, RE (2004) The medial temporal lobe. Ann Rev Neurosci 27, 279306.Google Scholar
78.Zola-Morgan, SM & Squire, LR (1990) The primate hippocampal formation: evidence for a time-limited role in memory storage. Science 250, 288290.Google Scholar
79.King, JA, Burgess, N, Hartley, T et al. (2002) Human hippocampus and viewpoint dependence in spatial memory. Hippocampus 12, 811820.Google Scholar
80.Burgess, N, Maguire, EA & O'Keefe, J (2002) The human hippocampus and spatial and episodic memory. Neuron 35, 625641.Google Scholar
81.O'Keefe, J (1984) Spatial memory within and without the hippocampal system. In Neurobiology of the Hippocampus, pp. 375403 [Seifert, W]. London: Academic Press.Google Scholar
82.Poucet, B & Benhamou, S (1997) The neuropsychology of spatial cognition in the rat. Crit Rev Neurobiol 11, 101120.Google Scholar
83.Shrager, Y, Bayley, PJ, Bontempi, B et al. (2007) Spatial memory and the human hippocampus. Proc Natl Acad Sci USA 104, 29612966.Google Scholar
84.Kesner, RP & Hopkins, RO (2006), Mnemonic functions of the hippocampus: A comparison between animals and humans. Biol Psychol 73, 3–18.Google Scholar
85.Astur, RS, Taylor, LB, Mamelak, AN et al. (2002) Humans with hippocampus damage display severe spatial memory impairments in a virtual Morris water task. Behav Brain Res 132, 7784.CrossRefGoogle Scholar
86.Olton, DS & Samuelson, RJ (1976) Remembrance of places past – spatial memory in rats. J Exp Psychol Anim Behav Process 2, 97–116.Google Scholar
87.Morris, R (1984) Developments of a water-maze procedure for studying spatial learning in the rat. J Neurosci Methods 11, 4760.Google Scholar
88.Olton, DS & Papas, BC (1979) Spatial memory and hippocampal function. Neuropsychologia 17, 669682.Google Scholar
89.Sutherland, RJ, Kolb, B, Whishaw, IQ et al. (1982) Cortical noradrenaline depletion eliminates sparing of spatial-learning after neonatal frontal-cortex damage in the rat. Neurosci Lett 32, 125130.Google Scholar
90.Bannerman, DM, Yee, BK, Good, MA et al. (1999) Double dissociation of function within the hippocampus: a comparison of dorsal, ventral and complete hippocampal cytotoxic lesions. Behav Neurosci 113, 11701188.Google Scholar
91.Barnes, CA (1990) Animal models of age-related cognitive decline. In Handbook of Neuropsychology, pp. 169196 [Boller, F and Grafman, J]. Amsterdam: Elsevier.Google Scholar
92.Barnes, CA (1979) Memory deficits associated with senescence: a neurophysiological and behavioral study in the rat. J Comp Physiol Psychol 93, 74–104.CrossRefGoogle ScholarPubMed
93.Moffat, SD, Zonderman, AB & Resnick, SM (2001) Age differences in spatial memory in a virtual environment navigation task. Neurobiol Aging 22, 787796.Google Scholar
94.Gallagher, M, Burwell, R & Burchinall, M (1993) Severity of spatial learning impairments in aging: development of a learning index for performance in the Morris Water Maze. Behav Neurosci 107, 618636.Google Scholar
95.Wilson, IA, Ikonen, S, Gallagher, M et al. (2005) Age-associated alterations of hippocampal place cells are subregion specific. J Neurosci 25, 68776886.Google Scholar
96.Li, Q, Zhao, HF, Zhang, ZF et al. (2009) Long-term green tea catechin administration prevents spatial learning and memory impairment in senescence-accelerated mouse prone-8 mice by decreasing Abeta1–42 oligomers and upregulating synaptic plasticity-related proteins in the hippocampus. Neuroscience 163, 741749.CrossRefGoogle ScholarPubMed
97.McGaugh, JL (2000) Memory – a century of consolidation. Science 287, 248251.Google Scholar
98.Lamprecht, R & LeDoux, J (2004) Structural plasticity and memory. Nat Rev Neurosci 5, 4554.Google Scholar
99.Muller, D, Nikonenko, I, Jourdain, P et al. (2002) LTP, memory and structural plasticity. Curr Mol Med 2, 605611.Google Scholar
100.Malenka, RC & Nicoll, RA (1999) Long-term potentiation – a decade of progress? Science 285, 18701874.Google Scholar
101.Bliss, TV & Collingridge, GL (1993) A synaptic model of memory: long-term potentiation in the hippocampus. Nature 361, 3139.Google Scholar
102.Lynch, G, Rex, CS & Gall, CM (2007) LTP consolidation: substrates, explanatory power, and functional significance. Neuropharmacology 52, 1223.Google Scholar
103.Kandel, ER (2001) The molecular biology of memory storage: a dialogue between genes and synapses. Science 294, 10301038.Google Scholar
104.Arnsten, AF, Ramos, BP, Birnbaum, SG et al. (2005) Protein kinase A as a therapeutic target for memory disorders: rationale and challenges. Trends Mol Med 11, 121128.Google Scholar
105.van der Heide, LP, Ramakers, GM & Smidt, MP (2006) Insulin signaling in the central nervous system: learning to survive. Prog Neurobiol 79, 205221.CrossRefGoogle ScholarPubMed
106.Kumar, V, Zhang, MX, Swank, MW et al. (2005) Regulation of dendritic morphogenesis by Ras-PI3K-Akt-mTOR and Ras-MAPK signaling pathways. J Neurosci 25, 1128811299.Google Scholar
107.Alkon, DL, Sun, MK & Nelson, TJ (2007) PKC signaling deficits: a mechanistic hypothesis for the origins of Alzheimer's disease. Trends Pharmacol Sci 28, 5160.Google Scholar
108.Bach, ME, Hawkins, RD, Osman, M et al. (1995) Impairment of spatial but not contextual memory in CaMKII mutant mice with a selective loss of hippocampal LTP in the range of the theta frequency. Cell 81, 905915.Google Scholar
109.Lisman, J, Schulman, H & Cline, H (2002) The molecular basis of CaMKII function in synaptic and behavioural memory. Nat Rev Neurosci 3, 175190.Google Scholar
110.Sweatt, JD (2001) The neuronal MAP kinase cascade: a biochemical signal integration system subserving synaptic plasticity and memory. J Neurochem 76, 110.Google Scholar
111.Sweatt, JD (2004) Mitogen-activated protein kinases in synaptic plasticity and memory. Curr Opin Neurobiol 14, 311317.Google Scholar
112.Esteban, JA, Shi, SH, Wilson, C et al. (2003) PKA phosphorylation of AMPA receptor subunits controls synaptic trafficking underlying plasticity. Nat Neurosci 6, 136143.Google Scholar
113.Kim, MJ, Dunah, AW, Wang, YT et al. (2005) Differential roles of NR2A- and NR2B-containing NMDA receptors in Ras-ERK signaling and AMPA receptor trafficking. Neuron 46, 745760.Google Scholar
114.Malinow, R & Malenka, RC (2002) AMPA receptor trafficking and synaptic plasticity. Annu Rev Neurosci 25, 103126.CrossRefGoogle ScholarPubMed
115.Zhu, JJ, Qin, Y, Zhao, M et al. (2002) Ras and Rap control AMPA receptor trafficking during synaptic plasticity. Cell 110, 443455.Google Scholar
116.Kelleher, RJ III, Govindarajan, A, Jung, HY et al. (2004) Translational control by MAPK signaling in long-term synaptic plasticity and memory. Cell 116, 467479.Google Scholar
117.Bozon, B, Kelly, A, Josselyn, SA et al. (2003) MAPK, CREB and zif268 are all required for the consolidation of recognition memory. Philos Trans R Soc Lond B Biol Sci 358, 805814.Google Scholar
118.Davis, HP & Squire, LR (1984) Protein synthesis and memory: a review. Psychol Bull 96, 518559.Google Scholar
119.Goelet, P, Castellucci, VF, Schacher, S et al. (1986) The long and the short of long-term memory – a molecular framework. Nature 322, 419422.Google Scholar
120.Hoeffer, CA & Klann, E (2010) mTOR signaling: at the crossroads of plasticity, memory and disease. Trends Neurosci 33, 6775.Google Scholar
121.Bekinschtein, P, Katche, C, Slipczuk, LN et al. (2007) mTOR signaling in the hippocampus is necessary for memory formation. Neurobiol Learn Mem 87, 303307.Google Scholar
122.Hou, L & Klann, E (2004) Activation of the phosphoinositide 3-kinase–Akt–mammalian target of rapamycin signaling pathway is required for metabotropic glutamate receptor-dependent long-term depression. J Neurosci 24, 63526361.Google Scholar
123.Brightwell, JJ, Smith, CA, Neve, RL et al. (2007) Long-term memory for place learning is facilitated by expression of cAMP response element-binding protein in the dorsal hippocampus. Learn Mem 14, 195199.Google Scholar
124.Sekeres, MJ, Neve, RL, Frankland, PW et al. (2010) Dorsal hippocampal CREB is both necessary and sufficient for spatial memory. Learn Mem 17, 280283.Google Scholar
125.Barco, A, Pittenger, C & Kandel, ER (2003) CREB, memory enhancement and the treatment of memory disorders: promises, pitfalls and prospects. Expert Opin Ther Targets 7, 101114.Google Scholar
126.Impey, S, McCorkle, SR, Cha-Molstad, H et al. (2004) Defining the CREB regulon: a genome-wide analysis of transcription factor regulatory regions. Cell 119, 10411054.Google Scholar
127.Impey, S, Smith, DM, Obrietan, K et al. (1998) Stimulation of cAMP response element (CRE)-mediated transcription during contextual learning. Nat Neurosci 1, 595601.Google Scholar
128.Leil, TA, Ossadtchi, A, Nichols, TE et al. (2003) Genes regulated by learning in the hippocampus. J Neurosci Res 71, 763768.Google Scholar
129.Finkbeiner, S (2000) CREB couples neurotrophin signals to survival messages. Neuron 25, 1114.Google Scholar
130.Lonze, BE & Ginty, DD (2002) Function and regulation of CREB family transcription factors in the nervous system. Neuron 35, 605623.Google Scholar
131.McAllister, AK, Katz, LC & Lo, DC (1999) Neurotrophins and synaptic plasticity. Annu Rev Neurosci 22, 295318.Google Scholar
132.Poo, MM (2001) Neurotrophins as synaptic modulators. Nat Rev Neurosci 2, 2432.Google Scholar
133.Cohen-Cory, S & Fraser, SE (1995) Effects of brain-derived neurotrophic factor on optic axon branching and remodelling in vivo. Nature 378, 192196.Google Scholar
134.Lu, B (2003) BDNF and activity-dependent synaptic modulation. Learn Mem 10, 8698.Google Scholar
135.Thomas, K & Davies, A (2005) Neurotrophins: a ticket to ride for BDNF. Curr Biol 15, R262R264.Google Scholar
136.Bailey, CH & Kandel, ER (1993) Structural changes accompanying memory storage. Annu Rev Physiol 55, 397426.Google Scholar
137.Tanaka, J, Horiike, Y, Matsuzaki, M et al. (2008) Protein synthesis and neurotrophin-dependent structural plasticity of single dendritic spines. Science 319, 16831687.Google Scholar
138.Nimchinsky, EA, Sabatini, BL & Svoboda, K (2002) Structure and function of dendritic spines. Annu Rev Physiol 64, 313353.Google Scholar
139.Fischer, M, Kaech, S, Wagner, U et al. (2000) Glutamate receptors regulate actin-based plasticity in dendritic spines. Nat Neurosci 3, 887894.Google Scholar
140.Messaoudi, E, Kanhema, T, Soule, J et al. (2007) Sustained Arc/Arg3.1 synthesis controls long-term potentiation consolidation through regulation of local actin polymerization in the dentate gyrus in vivo. J Neurosci 27, 1044510455.CrossRefGoogle ScholarPubMed
141.Tzingounis, AV & Nicoll, RA (2006) Arc/Arg3.1: linking gene expression to synaptic plasticity and memory. Neuron 52, 403407.Google Scholar
142.Bonfanti, L (2006) PSA-NCAM in mammalian structural plasticity and neurogenesis. Prog Neurobiol 80, 129164.Google Scholar
143.Dityatev, A, Dityateva, G, Sytnyk, V et al. (2004) Polysialylated neural cell adhesion molecule promotes remodeling and formation of hippocampal synapses. J Neurosci 24, 93729382.Google Scholar
144.Gascon, E, Vutskits, L & Kiss, JZ (2007) Polysialic acid-neural cell adhesion molecule in brain plasticity: from synapses to integration of new neurons. Brain Res Rev 56, 101118.CrossRefGoogle ScholarPubMed
145.Kiss, JZ, Troncoso, E, Djebbara, Z et al. (2001) The role of neural cell adhesion molecules in plasticity and repair. Brain Res Brain Res Rev 36, 175184.Google Scholar
146.Li, Q, Zhao, HF, Zhang, ZF et al. (2009) Long-term administration of green tea catechins prevents age-related spatial learning and memory decline in C57BL/6J mice by regulating hippocampal cyclic amp-response element binding protein signaling cascade. Neuroscience 159, 12081215.CrossRefGoogle Scholar
147.Winter, JC (1998) The effects of an extract of Ginkgo biloba, EGb 761, on cognitive behavior and longevity in the rat. Physiol Behav 63, 425433.Google Scholar
148.Rice-Evans, C (2001) Flavonoid antioxidants. Curr Med Chem 8, 797807.Google Scholar
149.Williams, RJ, Spencer, JP & Rice-Evans, C (2004) Flavonoids: antioxidants or signalling molecules? Free Radic Biol Med 36, 838849.Google Scholar
150.Goyarzu, P, Malin, DH, Lau, FC et al. (2004) Blueberry supplemented diet: effects on object recognition memory and nuclear factor-kappa B levels in aged rats. Nutr Neurosci 7, 7583.Google Scholar
151.Galli, RL, Bielinski, DF, Szprengiel, A et al. (2006) Blueberry supplemented diet reverses age-related decline in hippocampal HSP70 neuroprotection. Neurobiol Aging 27, 344350.Google Scholar
152.Shukitt-Hale, B, Lau, FC, Carey, AN et al. (2008) Blueberry polyphenols attenuate kainic acid-induced decrements in cognition and alter inflammatory gene expression in rat hippocampus. Nutr Neurosci 11, 172182.Google Scholar
153.Mandel, SA, Amit, T, Kalfon, L et al. (2008) Targeting multiple neurodegenerative diseases etiologies with multimodal-acting green tea catechins. J Nutr 138, 1578S1583S.Google Scholar
154.Mandel, SA, Avramovich-Tirosh, Y, Reznichenko, L et al. (2005) Multifunctional activities of green tea catechins in neuroprotection. Modulation of cell survival genes, iron-dependent oxidative stress and PKC signaling pathway. Neurosignals 14, 4660.Google Scholar
155.Khokhar, S & Magnusdottir, SG (2002) Total phenol, catechin, and caffeine contents of teas commonly consumed in the United kingdom. J Agric Food Chem 50, 565570.Google Scholar
156.Higdon, JV & Frei, B (2003) Tea catechins and polyphenols: health effects, metabolism, and antioxidant functions. Crit Rev Food Sci Nutr 43, 89–143.Google Scholar
157.Graham, HN (1992) Green tea composition, consumption, and polyphenol chemistry. Prev Med 21, 334350.CrossRefGoogle ScholarPubMed
158.Kim, HK, Kim, M, Kim, S et al. (2004) Effects of green tea polyphenol on cognitive and acetylcholinesterase activities. Biosci Biotechnol Biochem 68, 19771979.Google Scholar
159.Hu, G, Bidel, S, Jousilahti, P et al. (2007) Coffee and tea consumption and the risk of Parkinson's disease. Mov Disord 22, 22422248.Google Scholar
160.Assuncao, M, Santos-Marques, MJ, Carvalho, F et al. (2011) Chronic green tea consumption prevents age-related changes in rat hippocampal formation. Neurobiol Aging 32, 707717.Google Scholar
161.Nanjo, F, Goto, K, Seto, R et al. (1996) Scavenging effects of tea catechins and their derivatives on 1,1-diphenyl-2-picrylhydrazyl radical. Free Radic Biol Med 21, 895902.Google Scholar
162.Grinberg, LN, Newmark, H, Kitrossky, N et al. (1997) Protective effects of tea polyphenols against oxidative damage to red blood cells. Biochem Pharmacol 54, 973978.Google Scholar
163.Guo, Q, Zhao, B, Li, M et al. (1996) Studies on protective mechanisms of four components of green tea polyphenols against lipid peroxidation in synaptosomes. Biochim Biophys Acta 1304, 210222.Google Scholar
164.Aktas, O, Prozorovski, T, Smorodchenko, A et al. (2004) Green tea epigallocatechin-3-gallate mediates T cellular NF-kappa B inhibition and exerts neuroprotection in autoimmune encephalomyelitis. J Immunol 173, 57945800.Google Scholar
165.Lee, S, Suh, S & Kim, S (2000) Protective effects of the green tea polyphenol (−)-epigallocatechin gallate against hippocampal neuronal damage after transient global ischemia in gerbils. Neurosci Lett 287, 191194.Google Scholar
166.Weinreb, O, Amit, T & Youdim, MB (2007) A novel approach of proteomics and transcriptomics to study the mechanism of action of the antioxidant-iron chelator green tea polyphenol ( −)-epigallocatechin-3-gallate. Free Radic Biol Med 43, 546556.Google Scholar
167.Mandel, SA, Amit, T, Weinreb, O et al. (2008) Simultaneous manipulation of multiple brain targets by green tea catechins: a potential neuroprotective strategy for Alzheimer and Parkinson diseases. CNS Neurosci Ther 14, 352365.Google Scholar
168.Choi, YT, Jung, CH, Lee, SR et al. (2001) The green tea polyphenol (−)-epigallocatechin gallate attenuates beta-amyloid-induced neurotoxicity in cultured hippocampal neurons. Life Sci 70, 603614.CrossRefGoogle ScholarPubMed
169.Mandel, S, Maor, G & Youdim, MB (2004) Iron and alpha-synuclein in the substantia nigra of MPTP-treated mice: effect of neuroprotective drugs R-apomorphine and green tea polyphenol (−)-epigallocatechin-3-gallate. J Mol Neurosci 24, 401416.Google Scholar
170.Chen, C, Yu, R, Owuor, ED et al. (2000) Activation of antioxidant-response element (ARE), mitogen-activated protein kinases (MAPKs) and caspases by major green tea polyphenol components during cell survival and death. Arch Pharm Res 23, 605612.Google Scholar
171.Levites, Y, Amit, T, Youdim, MB et al. (2002) Involvement of protein kinase C activation and cell survival/cell cycle genes in green tea polyphenol (−)-epigallocatechin 3-gallate neuroprotective action. J Biol Chem 277, 3057430580.Google Scholar
172.Koh, SH, Kim, SH, Kwon, H et al. (2003) Epigallocatechin gallate protects nerve growth factor differentiated PC12 cells from oxidative-radical-stress-induced apoptosis through its effect on phosphoinositide 3-kinase/Akt and glycogen synthase kinase-3. Brain Res Mol Brain Res 118, 7281.Google Scholar
173.Levites, Y, Amit, T, Mandel, S et al. (2003) Neuroprotection and neurorescue against Abeta toxicity and PKC-dependent release of nonamyloidogenic soluble precursor protein by green tea polyphenol (−)-epigallocatechin-3-gallate. FASEB J 17, 952954.Google Scholar
174.Kalfon, L, Youdim, MB & Mandel, SA (2007) Green tea polyphenol (−)-epigallocatechin-3-gallate promotes the rapid protein kinase C- and proteasome-mediated degradation of Bad: implications for neuroprotection. J Neurochem 100, 992–1002.Google Scholar
175.Maher, P (2001) How protein kinase C activation protects nerve cells from oxidative stress-induced cell death. J Neurosci 21, 29292938.Google Scholar
176.Dempsey, EC, Newton, AC, Mochly-Rosen, D et al. (2000) Protein kinase C isozymes and the regulation of diverse cell responses. Am J Physiol Lung Cell Mol Physiol 279, L429L438.Google Scholar
177.Sun, MK, Hongpaisan, J & Alkon, DL (2009) Postischemic PKC activation rescues retrograde and anterograde long-term memory. Proc Natl Acad Sci USA 106, 1467614680.Google Scholar
178.Hongpaisan, J, Sun, MK & Alkon, DL (2011) PKC epsilon activation prevents synaptic loss, Abeta elevation, and cognitive deficits in Alzheimer's disease transgenic mice. J Neurosci 31, 630643.Google Scholar
179.Sun, MK & Alkon, DL (2010) Pharmacology of protein kinase C activators: cognition-enhancing and antidementic therapeutics. Pharmacol Ther 127, 6677.Google Scholar
180.Joseph, JA, Denisova, NA, Arendash, G et al. (2003) Blueberry supplementation enhances signaling and prevents behavioral deficits in an Alzheimer disease model. Nutr Neurosci 6, 153162.Google Scholar
181.Joseph, JA, Shukitt-Hale, B, Denisova, NA et al. (1998) Long-term dietary strawberry, spinach, or vitamin E supplementation retards the onset of age-related neuronal signal-transduction and cognitive behavioral deficits. J Neurosci 18, 80478055.Google Scholar
182.Shukitt-Hale, B, Cheng, V & Joseph, JA (2009) Effects of blackberries on motor and cognitive function in aged rats. Nutr Neurosci 12, 135140.Google Scholar
183.Shukitt-Hale, B, Cheng, V, Bielinski, D et al. (2006) Differential brain regional specificity to blueberry and strawberry polyphenols in improved motor and cognitive function in aged rats. Soc Neurosci Abstr 32, 81.15.Google Scholar
184.Borges, G, Degeneve, A, Mullen, W et al. (2010) Identification of flavonoid and phenolic antioxidants in black currants, blueberries, raspberries, red currants, and cranberries. J Agric Food Chem 58, 39013909.Google Scholar
185.Shukitt-Hale, B, Galli, RL, Meterko, V et al. (2005) Dietary supplementation with fruit polyphenolics ameliorates age-related deficits in behavior and neuronal markers of inflammation and oxidative stress. Age 27, 4957.Google Scholar
186.Ramirez, MR, Izquierdo, I, do Carmo Bassols Raseira, M et al. (2005) Effect of lyophilised Vaccinium berries on memory, anxiety and locomotion in adult rats. Pharmacol Res 52, 457462.Google Scholar
187.Shukitt-Hale, B, Carey, AN, Jenkins, D et al. (2007) Beneficial effects of fruit extracts on neuronal function and behavior in a rodent model of accelerated aging. Neurobiol Aging 28, 11871194.Google Scholar
188.Coultrap, SJ, Bickford, PC & Browning, MD (2008) Blueberry-enriched diet ameliorates age-related declines in NMDA receptor-dependent LTP. Age (Dordr) 30, 263272.Google Scholar
189.Drapeau, E, Mayo, W, Aurousseau, C et al. (2003) Spatial memory performances of aged rats in the water maze predict levels of hippocampal neurogenesis. Proc Natl Acad Sci USA 100, 1438514390.Google Scholar
190.Drapeau, E, Montaron, MF, Aguerre, S et al. (2007) Learning-induced survival of new neurons depends on the cognitive status of aged rats. J Neurosci 27, 60376044.Google Scholar
191.Kempermann, G & Gage, FH (2002) Genetic determinants of adult hippocampal neurogenesis correlate with acquisition, but not probe trial performance, in the water maze task. Eur J Neurosci 16, 129136.Google Scholar
192.Kempermann, G, Kuhn, HG & Gage, FH (1998) Experience-induced neurogenesis in the senescent dentate gyrus. J Neurosci 18, 32063212.Google Scholar
193.Nilsson, M, Perfilieva, E, Johansson, U et al. (1999) Enriched environment increases neurogenesis in the adult rat dentate gyrus and improves spatial memory. J Neurobiol 39, 569578.Google Scholar
194.Shors, TJ, Miesegaes, G, Beylin, A et al. (2001) Neurogenesis in the adult is involved in the formation of trace memories. Nature 410, 372376.Google Scholar
195.Shors, TJ, Townsend, DA, Zhao, M et al. (2002) Neurogenesis may relate to some but not all types of hippocampal-dependent learning. Hippocampus 12, 578584.Google Scholar
196.van Praag, H (2008) Neurogenesis and exercise: past and future directions. Neuromol Med 10, 128140.Google Scholar
197.DeFeudis, FV & Drieu, K (2000) Ginkgo biloba extract (EGb 761) and CNS functions: basic studies and clinical applications. Curr Drug Targets 1, 2558.Google Scholar
198.Le Bars, PL, Katz, MM, Berman, N et al. (1997) A placebo-controlled, double-blind, randomized trial of an extract of Ginkgo biloba for dementia. North American EGb Study Group. JAMA 278, 13271332.Google Scholar
199.Hoerr, R (2003) Behavioural and psychological symptoms of dementia (BPSD): effects of EGb 761. Pharmacopsychiatry 36, Suppl. 1, S56S61.Google Scholar
200.Kanowski, S & Hoerr, R (2003) Ginkgo biloba extract EGb 761 in dementia: intent-to-treat analyses of a 24-week, multi-center, double-blind, placebo-controlled, randomized trial. Pharmacopsychiatry 36, 297303.Google Scholar
201.Kanowski, S, Herrmann, WM, Stephan, K et al. (1996) Proof of efficacy of the Ginkgo biloba special extract EGb 761 in outpatients suffering from mild to moderate primary degenerative dementia of the Alzheimer type or multi-infarct dementia. Pharmacopsychiatry 29, 4756.Google Scholar
202.Chan, PC, Xia, Q & Fu, PP (2007) Ginkgo biloba leave extract: biological, medicinal, and toxicological effects. J Environ Sci Health C Environ Carcinog Ecotoxicol Rev 25, 211244.Google Scholar
203.Le Bars, PL, Velasco, FM, Ferguson, JM et al. (2002) Influence of the severity of cognitive impairment on the effect of the Ginkgo biloba extract EGb 761 in Alzheimer's disease. Neuropsychobiology 45, 1926.Google Scholar
204.Oken, BS, Storzbach, DM & Kaye, JA (1998) The efficacy of Ginkgo biloba on cognitive function in Alzheimer disease. Arch Neurol 55, 14091415.Google Scholar
205.Sierpina, VS, Wollschlaeger, B & Blumenthal, M (2003) Ginkgo biloba. Am Fam Phys 68, 923926.Google Scholar
206.Winter, E (1991) Effects of an extract of Ginkgo biloba on learning and memory in mice. Pharmacol Biochem Behav 38, 109114.Google Scholar
207.Topic, B, Hasenohrl, RU, Hacker, R et al. (2002) Enhanced conditioned inhibitory avoidance by a combined extract of Zingiber officinale and Ginkgo biloba. Phytother Res 16, 312315.Google Scholar
208.Hoffman, JR, Donato, A & Robbins, SJ (2004) Ginkgo biloba promotes short-term retention of spatial memory in rats. Pharmacol Biochem Behav 77, 533539.Google Scholar
209.Walesiuk, A, Trofimiuk, E & Braszko, JJ (2006) Ginkgo biloba normalizes stress- and corticosterone-induced impairment of recall in rats. Pharmacol Res 53, 123128.Google Scholar
210.Blecharz-Klin, K, Piechal, A, Joniec, I et al. (2009) Pharmacological and biochemical effects of Ginkgo biloba extract on learning, memory consolidation and motor activity in old rats. Acta Neurobiol Exp (Wars) 69, 217231.Google Scholar
211.Huang, SH, Duke, RK, Chebib, M et al. (2004) Ginkgolides, diterpene trilactones of Ginkgo biloba, as antagonists at recombinant alpha1beta2gamma2L GABAA receptors. Eur J Pharmacol 494, 131138.Google Scholar
212.Hadjiivanova, CI & Petkov, VV (2002) Effect of Ginkgo biloba extract on beta-adrenergic receptors in different rat brain regions. Phytother Res 16, 488490.Google Scholar
213.Ivic, L, Sands, TT, Fishkin, N et al. (2003) Terpene trilactones from Ginkgo biloba are antagonists of cortical glycine and GABA(A) receptors. J Biol Chem 278, 4927949285.Google Scholar
214.Williams, B, Watanabe, CM, Schultz, PG et al. (2004) Age-related effects of Ginkgo biloba extract on synaptic plasticity and excitability. Neurobiol Aging 25, 955962.Google Scholar
215.Tchantchou, F, Xu, Y, Wu, Y et al. (2007) EGb 761 enhances adult hippocampal neurogenesis and phosphorylation of CREB in transgenic mouse model of Alzheimer's disease. FASEB J 21, 24002408.Google Scholar
216.Watanabe, CM, Wolffram, S, Ader, P et al. (2001) The in vivo neuromodulatory effects of the herbal medicine Ginkgo biloba. Proc Natl Acad Sci USA 98, 65776580.Google Scholar
217.Wang, Y, Wang, L, Wu, J et al. (2006) The in vivo synaptic plasticity mechanism of EGb 761-induced enhancement of spatial learning and memory in aged rats. Br J Pharmacol 148, 147153.Google Scholar
218.Maher, P, Akaishi, T & Abe, K (2006) Flavonoid fisetin promotes ERK-dependent long-term potentiation and enhances memory. Proc Natl Acad Sci USA 103, 1656816573.Google Scholar
219.Jin, CH, Shin, EJ, Park, JB et al. (2009) Fustin flavonoid attenuates beta-amyloid (1–42)-induced learning impairment. J Neurosci Res 87, 36583670.Google Scholar
220.Maher, P (2009) Modulation of multiple pathways involved in the maintenance of neuronal function during aging by fisetin. Genes Nutr 4(4), 297307.Google Scholar
221.Schroeter, H, Bahia, P, Spencer, JP et al. (2007) ( −)Epicatechin stimulates ERK-dependent cyclic AMP response element activity and up-regulates GluR2 in cortical neurons. J Neurochem 101, 15961606.Google Scholar
222.Spencer, JP, Rice-Evans, C & Williams, RJ (2003) Modulation of pro-survival Akt/protein kinase B and ERK1/2 signaling cascades by quercetin and its in vivo metabolites underlie their action on neuronal viability. J Biol Chem 278, 3478334793.Google Scholar
223.Weinreb, O, Amit, T & Youdim, MB (2008) The application of proteomics for studying the neurorescue activity of the polyphenol ( −)-epigallocatechin-3-gallate. Arch Biochem Biophys 476, 152160.Google Scholar
224.Tully, T, Bourtchouladze, R, Scott, R et al. (2003) Targeting the CREB pathway for memory enhancers. Nat Rev Drug Discov 2, 267277.Google Scholar
225.Radecki, DT, Brown, LM, Martinez, J et al. (2005) BDNF protects against stress-induced impairments in spatial learning and memory and LTP. Hippocampus 15, 246253.Google Scholar
226.Garzon, D, Yu, G & Fahnestock, M (2002) A new brain-derived neurotrophic factor transcript and decrease in brain-derived neurotrophic factor transcripts 1, 2 and 3 in Alzheimer's disease parietal cortex. J Neurochem 82, 10581064.Google Scholar
227.Hwang, IK, Yoo, KY, Jung, BK et al. (2006) Correlations between neuronal loss, decrease of memory, and decrease expression of brain-derived neurotrophic factor in the gerbil hippocampus during normal aging. Exp Neurol 201, 7583.Google Scholar
228.Laske, C, Banschbach, S, Stransky, E et al. . (2010) Exercise-induced normalization of decreased BDNF serum concentration in elderly women with remitted major depression. Int J Neuropsychopharmacol 13, 595602.Google Scholar
229.Laske, C, Stransky, E, Leyhe, T et al. (2006) Stage-dependent BDNF serum concentrations in Alzheimer's disease. J Neural Transm 113, 12171224.Google Scholar
230.Fumagalli, F, Racagni, G & Riva, MA (2006) The expanding role of BDNF: a therapeutic target for Alzheimer's disease? Pharmacogenomics J 6, 8–15.Google Scholar
231.Marvanova, M, Lakso, M, Pirhonen, J et al. (2001) The neuroprotective agent memantine induces brain-derived neurotrophic factor and trkB receptor expression in rat brain. Mol Cell Neurosci 18, 247258.Google Scholar
232.Lauterborn, JC, Lynch, G, Vanderklish, P et al. (2000) Positive modulation of AMPA receptors increases neurotrophin expression by hippocampal and cortical neurons. J Neurosci 20, 8–21.Google Scholar
233.Mackowiak, M, O'Neill, MJ, Hicks, CA et al. (2002) An AMPA receptor potentiator modulates hippocampal expression of BDNF: an in vivo study. Neuropharmacology 43, 110.Google Scholar
234.Burke, SN & Barnes, CA (2006) Neural plasticity in the ageing brain. Nat Rev Neurosci 7, 3040.Google Scholar
235.Gallagher, M (2003) Aging and hippocampal/cortical circuits in rodents. Alzheimer Dis Assoc Disord 17, Suppl. 2, S45S47.Google Scholar
Figure 0

Table 1. Structure of the main flavonoids present in the human diet

Figure 1

Fig. 1. Summary of the formation of metabolites and conjugates of flavonoids in human subjects. All classes of flavonoids undergo extensive phase II metabolism in the gastrointestinal tract and liver during which there is significant glucuronidation and sulfation of nearly all flavonoids by the action of uridine diphosphate-glucuronosyltransferase and sulfotransferase enzymes, respectively. There is also extensive O-methylation catalysed by the action of catechol-O-methyltransferase. Colonic microflora degrades flavonoids into smaller phenolic acids, such as phenylacetic acid, protocatechuic acid, phenylpropionic acid and benzoic acid, which may also be absorbed. Some of these metabolites are excreted through the kidneys. However, some may enter peripheral cells (e.g endothelial cells) and cross the blood–brain barrier and enter the brain. Flavonoids may then undergo further intracellular metabolism (phase III), usually oxidative metabolism, P450-related metabolism and conjugation with thiols.

Figure 2

Fig. 2. (A) Molecular mechanisms underlying synaptic plasticity processes. (i) Activity-dependent release from presynaptic neurons lead to activation of α-amino-3-hydroxy-5-methyllisoxazole-4-propionic acid receptors (AMPAR) that causes depolarisation of the postsynaptic neuron, resulting in activation of N-methyl-d-aspartate receptors (NMDAR) and Ca2+ influx. (ii) Ca influx causes activation of kinase signalling pathways, which induces activation of transcription factors and induces gene expression and new protein synthesis. (iii) This leads to stabilisation of synaptic changes and contributes to morphological changes at the synapse through regulation of the cytoskeleton which will ultimately impact on learning and retention of memories. (B) Signalling pathways involved in controlling memory and learning in the hippocampus. Activation of signalling pathways such as protein kinase A (PKA), protein kinase C (PKC ), protein kinase B (also known as Akt); extracellular-signal-regulated kinase 1/2 (ERK1/2) and Ca-calmodulin kinase (CamK) converge to activate the transcription factor cAMP response element-binding protein (CREB) that regulates the transcription of many genes associated with synapse re-modelling, synaptic plasticity and memory. PSA-NCAM, polysialylated-neural cell adhesion molecule; TrkB, truncated tyrosin kinase B receptor; BDNF, brain-derived neurotrophic factor.

Figure 3

Table 2. Effects of flavonoid-rich foods (Gingko biloba, green tea and blueberries) on memory and learning in rodents

Figure 4

Table 3. Effects of pure flavonoids on memory and learning in rodents