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.

The effect of learning condition on perceptual anticipation, awareness, and visual search

The efficacy of explicit and implicit learning paradigms was examined during the very early stages of learning the perceptual-motor anticipation task of predicting ball direction from temporally occluded footage of soccer penalty kicks. In addition, the effect of instructional condition on point-of-gaze during learning was examined. A significant improvement in horizontal prediction accuracy was observed in the explicit learning group; however, similar improvement was evident in a placebo group who watched footage of soccer matches. Only the explicit learning intervention resulted in changes in eye movement behaviour and increased awareness of relevant postural cues. Results are discussed in terms of methodological and practical issues regarding the employment of implicit perceptual training interventions. (c) 2005 Elsevier B.V. All rights reserved.

The use of social and salience cues in early word learning

This article explores young infants' ability to learn new words in situations providing tightly controlled social and salience cues to their reference. Four experiments investigated whether, given two potential referents, 15-month-olds would attach novel labels to (a) an image toward which a digital recording of a face turned and gazed, (b) a moving image versus a stationary image, (c) a moving image toward which the face gazed, and (d) a gazed-on image versus a moving image. Infants successfully used the recorded gaze cue to form new word-referent associations and also showed learning in the salience condition. However, their behavior in the salience condition and in the experiments that followed suggests that, rather than basing their judgments of the words' reference on the mere presence or absence of the referent's motion, infants were strongly biased to attend to the consistency with which potential referents moved when a word was heard. (c) 2006 Elsevier Inc. All rights reserved.

B-spline neural network based digital baseband predistorter solution using the inverse of De Boor algorithm

In this paper a new nonlinear digital baseband predistorter design is introduced based on direct learning, together with a new Wiener system modeling approach for the high power amplifiers (HPA) based on the B-spline neural network. The contribution is twofold. Firstly, by assuming that the nonlinearity in the HPA is mainly dependent on the input signal amplitude the complex valued nonlinear static function is represented by two real valued B-spline neural networks, one for the amplitude distortion and another for the phase shift. The Gauss-Newton algorithm is applied for the parameter estimation, in which the De Boor recursion is employed to calculate both the B-spline curve and the first order derivatives. Secondly, we derive the predistorter algorithm calculating the inverse of the complex valued nonlinear static function according to B-spline neural network based Wiener models. The inverse of the amplitude and phase shift distortion are then computed and compensated using the identified phase shift model. Numerical examples have been employed to demonstrate the efficacy of the proposed approaches.

Languages Learning at Key Stage 2. A Longitudinal Study. Final report.

In 2006, The Open University, the University of Southampton and Canterbury Christ Church University were commissioned by the then Department for Education and Skills (DfES), now Department for Children, Schools and Families (DCSF) to conduct a three-year longitudinal study of languages learning at Key Stage 2 (KS2). The qualitative study was designed to explore provision, practice and developments over three school years between 2006/07 and 2008/09 in a sample of primary schools and explore children’s achievement in oracy and literacy, as well as the possible broader cross-curricular impact of languages learning.

Achieving business and IT alignment from organisational learning perspectives

Business and IT alignment has continued as a top concern for business and IT executives for almost three decades. Many researchers have conducted empirical studies on the relationship between business-IT alignment and performance. Yet, these approaches, lacking a social perspective, have had little impact on sustaining performance and competitive advantage. In addition to the limited alignment literature that explores organisational learning that is represented in shared understanding, communication, cognitive maps and experiences. Hence, this paper proposes an integrated process that enables social and intellectual dimensions through the concept of organisational learning. In particular, the feedback and feed- forward process which provide a value creation across dynamic multilevel of learning. This mechanism enables on-going effectiveness through development of individuals, groups and organisations, which improves the quality of business and IT strategies and drives to performance.

Digital predistorter design using B-Spline neural network and inverse of De Boor algorithm

This contribution introduces a new digital predistorter to compensate serious distortions caused by memory high power amplifiers (HPAs) which exhibit output saturation characteristics. The proposed design is based on direct learning using a data-driven B-spline Wiener system modeling approach. The nonlinear HPA with memory is first identified based on the B-spline neural network model using the Gauss-Newton algorithm, which incorporates the efficient De Boor algorithm with both B-spline curve and first derivative recursions. The estimated Wiener HPA model is then used to design the Hammerstein predistorter. In particular, the inverse of the amplitude distortion of the HPA's static nonlinearity can be calculated effectively using the Newton-Raphson formula based on the inverse of De Boor algorithm. A major advantage of this approach is that both the Wiener HPA identification and the Hammerstein predistorter inverse can be achieved very efficiently and accurately. Simulation results obtained are presented to demonstrate the effectiveness of this novel digital predistorter design.