The influence of classical-conditioning procedures on subsequent attention to the conditioned brand.

Three experiments are used to investigate the influence of conditioning procedures on attention to a conditioned stimulus. In experiment 1, scenes presented in a sequence that is consistent with prescribed conditioning procedures are shown to encourage attention to the advertised brands in subsequent product displays. Experiment 2 suggests that differential attention to conditioned brands can be attributed to the signaling properties the brand acquires as a consequence of conditioning. Evidence from a third experiment raises the possibility that semantic conditioning may be responsible for the effects observed in experiments 1 and 2. The findings suggest that current prescriptions on the use of conditioning procedures may need to be updated.contingency awareness; orienting response; external validity; consumer research; context; stimulus; recall;

Pipelined genetic propagation

© 2015 IEEE.Genetic Algorithms (GAs) are a class of numerical and combinatorial optimisers which are especially useful for solving complex non-linear and non-convex problems. However, the required execution time often limits their application to small-scale or latency-insensitive problems, so techniques to increase the computational efficiency of GAs are needed. FPGA-based acceleration has significant potential for speeding up genetic algorithms, but existing FPGA GAs are limited by the generational approaches inherited from software GAs. Many parts of the generational approach do not map well to hardware, such as the large shared population memory and intrinsic loop-carried dependency. To address this problem, this paper proposes a new hardware-oriented approach to GAs, called Pipelined Genetic Propagation (PGP), which is intrinsically distributed and pipelined. PGP represents a GA solver as a graph of loosely coupled genetic operators, which allows the solution to be scaled to the available resources, and also to dynamically change topology at run-time to explore different solution strategies. Experiments show that pipelined genetic propagation is effective in solving seven different applications. Our PGP design is 5 times faster than a recent FPGA-based GA system, and 90 times faster than a CPU-based GA system

Synaptic metaplasticity underlies tetanic potentiation in Lymnaea: a novel paradigm

We present a mathematical model which explains and interprets a novel form of short-term potentiation, which was found to be use-, but not time-dependent, in experiments done on Lymnaea neurons. The high degree of potentiation is explained using a model of synaptic metaplasticity, while the use-dependence (which is critically reliant on the presence of kinase in the experiment) is explained using a model of a stochastic and bistable biological switch.Comment: 12 pages, 7 figures, to appear in PLoS One (2013

Selectivity and Metaplasticity in a Unified Calcium-Dependent Model

A unified, biophysically motivated Calcium-Dependent Learning model has been shown to account for various rate-based and spike time-dependent paradigms for inducing synaptic plasticity. Here, we investigate the properties of this model for a multi-synapse neuron that receives inputs with different spike-train statistics. In addition, we present a physiological form of metaplasticity, an activity-driven regulation mechanism, that is essential for the robustness of the model. A neuron thus implemented develops stable and selective receptive fields, given various input statistic

Non-linear function evaluation reusing matrix-vector multipliers

This paper presents a method to extend matrix-vector multipliers to support the evaluation of non-linear functions. The proposed approach introducesnon-linearity by optionally overriding the input sig-nals of the matrix-vector multiplier. The methodaims to reduce the idleness of hardware resources dur-ing computation, to maximise the reuse of arithmeticunits and internal structures in existing matrix-vectormultipliers, and to reduce the effort in adding addi-tional functions. From our analysis on a case witheight non-linear functions, the proposed design con-sumes fewer components for addition, multiplication,division, exponentiation and logarithm than a refer-ence design with dedicated function evaluation facil-ities

FLiMS: a fast lightweight 2-way merger for sorting

In this paper, we present FLiMS, a highly-efficient and simple parallel algorithm for merging two sorted lists residing in banked and/or wide memory. On FPGAs, its implementation uses fewer hardware resources than the state-of-the-art alternatives, due to the reduced number of comparators and elimination of redundant logic found on prior attempts. In combination with the distributed nature of the selector stage, a higher performance is achieved for the same amount of parallelism or higher. This is useful in many applications such as in parallel merge trees to achieve high-throughput sorting, where the resource utilisation of the merger is critical for building larger trees and internalising the workload for faster computation. Also presented are efficient variations of FLiMS for optimizing throughput for skewed datasets, achieving stable sorting or using fewer dequeue signals. FLiMS is also shown to perform well as conventional software on modern CPUs supporting single-instruction multiple-data (SIMD) instructions, surpassing the performance of some standard libraries for sorting