Optimal recall from bounded metaplastic synapses: predicting functional adaptations in hippocampal area CA3.

A venerable history of classical work on autoassociative memory has significantly shaped our understanding of several features of the hippocampus, and most prominently of its CA3 area, in relation to memory storage and retrieval. However, existing theories of hippocampal memory processing ignore a key biological constraint affecting memory storage in neural circuits: the bounded dynamical range of synapses. Recent treatments based on the notion of metaplasticity provide a powerful model for individual bounded synapses; however, their implications for the ability of the hippocampus to retrieve memories well and the dynamics of neurons associated with that retrieval are both unknown. Here, we develop a theoretical framework for memory storage and recall with bounded synapses. We formulate the recall of a previously stored pattern from a noisy recall cue and limited-capacity (and therefore lossy) synapses as a probabilistic inference problem, and derive neural dynamics that implement approximate inference algorithms to solve this problem efficiently. In particular, for binary synapses with metaplastic states, we demonstrate for the first time that memories can be efficiently read out with biologically plausible network dynamics that are completely constrained by the synaptic plasticity rule, and the statistics of the stored patterns and of the recall cue. Our theory organises into a coherent framework a wide range of existing data about the regulation of excitability, feedback inhibition, and network oscillations in area CA3, and makes novel and directly testable predictions that can guide future experiments.

Top down scale-up of semiconducting nanostructures for large area electronics

In this paper, we present a study on electrical and optical characteristics of n-type tin-oxide nanowires integrated based on top-down scale-up strategy. Through a combination of contact printing and plasma based back-channel passivation, we have achieved stable electrical characteristics with standard deviation in mobility and threshold voltage of 9.1% and 25%, respectively, for a large area of 1× 1 cm2 area. Through use of contact printing, high alignment of nanowires was achieved thus minimizing the number of nanowire-nanowire junctions, which serve to limit carrier transport in the channel. In addition, persistent photoconductivity has been observed, which we attribute to oxygen vacancy ionization and subsequent elimination using a gate pulse driving scheme. © 2014 IEEE.

Increased carbon nanotube area density after catalyst generation from cobalt disilicide using a cyclic reactive ion etching approach

We used a cyclic reactive ion etching (RIE) process to increase the Co catalyst density on a cobalt disilicide (CoSi2) substrate for carbon nanotube (CNT) growth. Each cycle of catalyst formation consists of a room temperature RIE step and an annealing step at 450 °C. The RIE step transfers the top-surface of CoSi2 into cobalt fluoride; while the annealing reduces the fluoride into metallic Co nanoparticles. We have optimized this cyclic RIE process and determined that the catalyst density can be doubled in three cycles, resulting in a final CNT shell density of 6.6 × 10 11 walls·cm-2. This work demonstrates a very effective approach to increase the CNT density grown directly on silicides. © 2014 AIP Publishing LLC.