The impact of flavonoids on memory: physiological and molecular considerations

Emerging evidence suggests that a group of dietary-derived phytochemicals known as flavonoids are able to induce improvements in memory acquisition, consolidation, storage and retrieval. These low molecular weight polyphenols are widespread in the human diet, are absorbed to only a limited degree and localise in the brain at low concentration. However, they have been found to be highly effective in reversing age-related declines in memory via their ability to interact with the cellular and molecular architecture of the brain responsible for memory. These interactions include an ability to activate signalling pathways, critical in controlling synaptic plasticity, and a potential to induce vascular effects capable of causing new nerve cell growth in the hippocampus. Their ability to activate the extracellular signal-regulated kinase (ERK1/2) and the protein kinase B (PKB/Akt) signalling pathways, leading to the activation of the cAMP response element-binding protein (CREB), a transcription factor responsible for increasing the expression of a number of neurotrophins important in de. ning memory, will be discussed. How these effects lead to improvements in memory through induction of synapse growth and connectivity, increases in dendritic spine density and the functional integration of old and new neurons will be illustrated. The overall goal of this critical review is to emphasize future areas of investigation as well as to highlight these dietary agents as promising candidates for the design of memory-enhancing drugs with relevance to normal and pathological brain ageing (161 references).

Food for thought: the role of dietary flavonoids in enhancing human memory, learning and neuro-cognitive performance

Emerging evidence suggests that dietary-derived flavonoids have the potential to improve human memory and neuro-cognitive performance via their ability to protect vulnerable neurons, enhance existing neuronal function and stimulate neuronal regeneration. Long-term potentiation (LTP) is widely considered to be one of the major mechanisms underlying memory acquisition, consolidation and storage in the brain and is known to be controlled at the molecular level by the activation of a number of neuronal signalling pathways. These pathways include the phosphatidylinositol-3 kinase/protein kinase B/Akt (Akt), protein kinase C, protein kinase A, Ca-calmodulin kinase and mitogen-activated protein kinase pathways. Growing evidence suggests that flavonoids exert effects on LTP, and consequently memory and cognitive performance, through their interactions with these signalling pathways. Of particular interest is the ability of flavonoids to activate the extracellular signal-regulated kinase and the Akt signalling pathways leading to the activation of the cAMP-response element-binding protein, a transcription factor responsible for increasing the expression of a number of neurotrophins important in LTP and long-term memory. One such neurotrophin is brain-derived neurotrophic factor, which is known to be crucial in controlling synapse growth, in promoting an increase in dendritic spine density and in enhancing synaptic receptor density. The present review explores the potential of flavonoids and their metabolite forms to promote memory and learning through their interactions with neuronal signalling pathways pivotal in controlling LTP and memory in human subjects.

Agonist-dependent internalization of D2 receptors: Imaging quantification by confocal microscopy

In positron emission tomography and single photon emission computed tomography studies using D2 dopamine (DA) receptor radiotracers, a decrease in radiotracer binding potential (BP) is usually interpreted in terms of increased competition with synaptic DA. However, some data suggest that this signal may also reflect agonist (DA)-induced increases in D2 receptor (D2R) internalization, a process which would presumably also decrease the population of receptors available for binding to hydrophilic radioligands. To advance interpretation of alterations in D2 radiotracer BP, direct methods of assessment of D2R internalization are required. Here, we describe a confocal microscopy-based approach for the quantification of agonist-dependent receptor internalization. The method relies upon double-labeling of the receptors with antibodies directed against intracellular as well as extracellular epitopes. Following agonist stimulation, DA D2R internalization was quantified by differentiating, in optical cell sections, the signal due to the staining of the extracellular from intracellular epitopes of D2Rs. Receptor internalization was increased in the presence of the D2 agonists DA and bromocriptine, but not the D1 agonist SKF38393. Pretreatment with either the D2 antagonist sulpiride, or inhibitors of internalization (phenylarsine oxide and high molarity sucrose), blocked D2-agonist induced receptor internalization, thus validating this method in vitro. This approach therefore provides a direct and streamlined methodology for investigating the pharmacological and mechanistic aspects of D2R internalization, and should inform the interpretation of results from in vivo receptor imaging studies.

The human thalamus processes syntactic and semantic language violations

Numerous linguistic operations have been assigned to cortical brain areas, but the contributions of subcortical structures to human language processing are still being discussed. Using simultaneous EEG recordings directly from deep brain structures and the scalp, we show that the human thalamus systematically reacts to syntactic and semantic parameters of auditorily presented language in a temporally interleaved manner in coordination with cortical regions. In contrast, two key structures of the basal ganglia, the globus pallidus internus and the subthalamic nucleus, were not found to be engaged in these processes. We therefore propose that syntactic and semantic language analysis is primarily realized within cortico-thalamic networks, whereas a cohesive basal ganglia network is not involved in these essential operations of language analysis.

Global exponential periodicity of a class of bidirectional associative memory networks with finite distributed delays

In this paper, we study the periodic oscillatory behavior of a class of bidirectional associative memory (BAM) networks with finite distributed delays. A set of criteria are proposed for determining global exponential periodicity of the proposed BAM networks, which assume neither differentiability nor monotonicity of the activation function of each neuron. In addition, our criteria are easily checkable. (c) 2005 Elsevier Inc. All rights reserved.

Global exponential periodicity of a class of neural networks with recent-history distributed delays

In this paper, we propose to study a class of neural networks with recent-history distributed delays. A sufficient condition is derived for the global exponential periodicity of the proposed neural networks, which has the advantage that it assumes neither the differentiability nor monotonicity of the activation function of each neuron nor the symmetry of the feedback matrix or delayed feedback matrix. Our criterion is shown to be valid by applying it to an illustrative system. (c) 2005 Elsevier Ltd. All rights reserved.

The 'glial' glutamate transporter, EAAT2 (Glt-1) accounts for high affinity glutamate uptake into adult rodent nerve endings

The excitatory amino acid transporters (EAAT) removes neurotransmitters glutamate and aspartate from the synaptic cleft. Most CNS glutamate uptake is mediated by EAAT2 into glia, though nerve terminals show evidence for uptake, through an unknown transporter. Reverse-transcriptase PCR identified the expression of EAAT1, EAAT2, EAAT3 and EAAT4 mRNAs in primary cultures of mouse cortical or striatal neurones. We have used synaptosomes and glial plasmalemmal vesicles (GPV) from adult mouse and rat CNS to identify the nerve terminal transporter. Western blotting showed detectable levels of the transporters EAAT1 (GLAST) and EAAT2 (Glt-1) in both synaptosomes and GPVs. Uptake of [3H]D-aspartate or [3H]L-glutamate into these preparations revealed sodium-dependent uptake in GPV and synaptosomes which was inhibited by a range of EAAT blockers: dihydrokainate, serine-o-sulfate, l-trans-2,4-pyrrolidine dicarboxylate (PDC) (+/-)-threo-3-methylglutamate and (2S,4R )-4-methylglutamate. The IC50 values found for these compounds suggested functional expression of the 'glial, transporter, EAAT2 in nerve terminals. Additionally blockade of the majority EAAT2 uptake sites with 100 micro m dihydrokainate, failed to unmask any functional non-EAAT2 uptake sites. The data presented in this study indicate that EAAT2 is the predominant nerve terminal glutamate transporter in the adult rodent CNS.

Intact imitation of emotional facial actions in autism spectrum conditions.

It has been proposed that there is a core impairment in autism spectrum conditions (ASC) to the mirror neuron system (MNS): If observed actions cannot be mapped onto the motor commands required for performance, higher order sociocognitive functions that involve understanding another person's perspective, such as theory of mind, may be impaired. However, evidence of MNS impairment in ASC is mixed. The present study used an 'automatic imitation' paradigm to assess MNS functioning in adults with ASC and matched controls, when observing emotional facial actions. Participants performed a pre-specified angry or surprised facial action in response to observed angry or surprised facial actions, and the speed of their action was measured with motion tracking equipment. Both the ASC and control groups demonstrated automatic imitation of the facial actions, such that responding was faster when they acted with the same emotional expression that they had observed. There was no difference between the two groups in the magnitude of the effect. These findings suggest that previous apparent demonstrations of impairments to the MNS in ASC may be driven by a lack of visual attention to the stimuli or motor sequencing impairments, and therefore that there is, in fact, no MNS impairment in ASC. We discuss these findings with reference to the literature on MNS functioning and imitation in ASC, as well as theories of the role of the MNS in sociocognitive functioning in typical development.

Dynamic knowledge representation in connectionist systems

One of the most pervading concepts underlying computational models of information processing in the brain is linear input integration of rate coded uni-variate information by neurons. After a suitable learning process this results in neuronal structures that statically represent knowledge as a vector of real valued synaptic weights. Although this general framework has contributed to the many successes of connectionism, in this paper we argue that for all but the most basic of cognitive processes, a more complex, multi-variate dynamic neural coding mechanism is required - knowledge should not be spacially bound to a particular neuron or group of neurons. We conclude the paper with discussion of a simple experiment that illustrates dynamic knowledge representation in a spiking neuron connectionist system.

Computer generation and quantitative morphometric analysis of virtual neurons

An important goal in computational neuroanatomy is the complete and accurate simulation of neuronal morphology. We are developing computational tools to model three-dimensional dendritic structures based on sets of stochastic rules. This paper reports an extensive, quantitative anatomical characterization of simulated motoneurons and Purkinje cells. We used several local and global algorithms implemented in the L-Neuron and ArborVitae programs to generate sets of virtual neurons. Parameters statistics for all algorithms were measured from experimental data, thus providing a compact and consistent description of these morphological classes. We compared the emergent anatomical features of each group of virtual neurons with those of the experimental database in order to gain insights on the plausibility of the model assumptions, potential improvements to the algorithms, and non-trivial relations among morphological parameters. Algorithms mainly based on local constraints (e.g., branch diameter) were successful in reproducing many morphological properties of both motoneurons and Purkinje cells (e.g. total length, asymmetry, number of bifurcations). The addition of global constraints (e.g., trophic factors) improved the angle-dependent emergent characteristics (average Euclidean distance from the soma to the dendritic terminations, dendritic spread). Virtual neurons systematically displayed greater anatomical variability than real cells, suggesting the need for additional constraints in the models. For several emergent anatomical properties, a specific algorithm reproduced the experimental statistics better than the others did. However, relative performances were often reversed for different anatomical properties and/or morphological classes. Thus, combining the strengths of alternative generative models could lead to comprehensive algorithms for the complete and accurate simulation of dendritic morphology.

Perspex machine X: software development

The Perspex Machine arose from the unification of computation with geometry. We now report significant redevelopment of both a partial C compiler that generates perspex programs and of a Graphical User Interface (GUI). The compiler is constructed with standard compiler-generator tools and produces both an explicit parse tree for C and an Abstract Syntax Tree (AST) that is better suited to code generation. The GUI uses a hash table and a simpler software architecture to achieve an order of magnitude speed up in processing and, consequently, an order of magnitude increase in the number of perspexes that can be manipulated in real time (now 6,000). Two perspex-machine simulators are provided, one using trans-floating-point arithmetic and the other using transrational arithmetic. All of the software described here is available on the world wide web. The compiler generates code in the neural model of the perspex. At each branch point it uses a jumper to return control to the main fibre. This has the effect of pruning out an exponentially increasing number of branching fibres, thereby greatly increasing the efficiency of perspex programs as measured by the number of neurons required to implement an algorithm. The jumpers are placed at unit distance from the main fibre and form a geometrical structure analogous to a myelin sheath in a biological neuron. Both the perspex jumper-sheath and the biological myelin-sheath share the computational function of preventing cross-over of signals to neurons that lie close to an axon. This is an example of convergence driven by similar geometrical and computational constraints in perspex and biological neurons.

Robotic movement elicits automatic imitation

Recent behavioural and neuroimaging studies have found that observation of human movement, but not of robotic movement, gives rise to visuomotor priming. This implies that the 'mirror neuron' or 'action observation–execution matching' system in the premotor and parietal cortices is entirely unresponsive to robotic movement. The present study investigated this hypothesis using an 'automatic imitation' stimulus–response compatibility procedure. Participants were required to perform a prespecified movement (e.g. opening their hand) on presentation of a human or robotic hand in the terminal posture of a compatible movement (opened) or an incompatible movement (closed). Both the human and the robotic stimuli elicited automatic imitation; the prespecified action was initiated faster when it was cued by the compatible movement stimulus than when it was cued by the incompatible movement stimulus. However, even when the human and robotic stimuli were of comparable size, colour and brightness, the human hand had a stronger effect on performance. These results suggest that effector shape is sufficient to allow the action observation–matching system to distinguish human from robotic movement. They also indicate, as one would expect if this system develops through learning, that to varying degrees both human and robotic action can be 'simulated' by the premotor and parietal cortices.

Modulation of neuroinflammation by dietary flavonoids

There is increasing evidence to suggest neuroinflammatory processes contribute to the cascade of events that lead to the progressive neuronal damage observed in neurodegenerative disorders such as Parkinson’s disease and Alzheimer’s disease. The molecular mechanisms underlying such neurodegenerative processes are rather complex and involve modulation of the mitogen-activated protein kinase (MAPK) and NF-κB pathways leading to the generation of nitric oxide (NO). Such a small molecule may diffuse to the neighbouring neurons and trigger neuronal death through the inhibition of mitochondrial respiration and increases in the reactive oxygen and nitrogen species. Recently, attention has focused on the neuroprotective effects of flavonoids which have been effective in protecting against both age-related cognitive and motor decline in vivo. Although, the precise mechanisms by which flavonoids may exert their neuroprotective effects remain unclear, accumulating evidence suggest that they may exert their neuroprotective effects through the modulation of the MAP Kinase and PI3 Kinase signaling pathways. The aim of the present chapter is to highlight the potential neuroprotective role of dietary flavonoids in terms of their ability to modulate neuroinflammation in the central nervous system. We will provide an outline of the role glial cells play in neuroinflammation and describe the involvement of inflammatory mediators, produced by glia, in the cascade of events leading to neuronal degeneration. We will then present the evidence that flavonoids may modulate neuroinflammation by inhibiting the production of these inflammatory agents and summarise their potential mechanisms of action.

Modular non-computational-connectionist-hybrid neural network approach to robotic systems

Spiking neural networks are usually limited in their applications due to their complex mathematical models and the lack of intuitive learning algorithms. In this paper, a simpler, novel neural network derived from a leaky integrate and fire neuron model, the ‘cavalcade’ neuron, is presented. A simulation for the neural network has been developed and two basic learning algorithms implemented within the environment. These algorithms successfully learn some basic temporal and instantaneous problems. Inspiration for neural network structures from these experiments are then taken and applied to process sensor information so as to successfully control a mobile robot.

Measuring the effects of manipulating stimulus presentation time on sensorimotor alpha and low beta reactivity during hand movement observation

The present study addresses three methodological questions that have been ignored in previous research on EEG indices of the human mirror neuron system (hMNS), particularly in regard to autistic individuals. The first question regards how to elicit the EEG indexed hMNS during movement observation: Is hMNS activation best elicited using long stimulus presentations or multiple short repetitions? The second question regards what EEG sensorimotor frequency bands reflect sensorimotor reactivity during hand movement observation? The third question regards how widespread is the EEG reactivity over the sensorimotor cortex during movement observation? The present study explored sensorimotor alpha and low beta reactivity during hand movement versus static hand or bouncing balls observation and compared two experimental protocols (long exposure vs. multiple repetitions) in the same participants. Results using the multiple repetitions protocol indicated a greater low beta desynchronisation over the sensorimotor cortex during hand movement compared to static hand and bouncing balls observation. This result was not achieved using the long exposure protocol. Therefore, the present study suggests that the multiple repetitions protocol is a more robust protocol to use when exploring the sensorimotor reactivity induced by hand action observation. In addition, sensorimotor low beta desynchronisation was differently modulated during hand movement, static hand and bouncing balls observation (non-biological motion) while it was not the case for sensorimotor alpha and that suggest that low beta may be a more sensitive index of hMNS activation during biological motion observation. In conclusion the present study indicates that sensorimotor reactivity of low beta during hand movement observation was found to be more widespread over the sensorimotor cortex than previously thought.