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.

Effect of process parameters on the morphology and nanostructure of roll-to-roll printed P3HT:PCBM thin films for organic photovoltaics

Roll-to-roll (R2R) gravure exhibits significant advantages such as high precision and throughput for the printing of photoactive and conductive materials and the fabrication of flexible organic electronics such as organic photovoltaics (OPVs). Since the photoactive layer is the core of the OPV, it is important to investigate and finally control the process parameters and mechanisms that define the film morphology in a R2R process. The scope of this work is to study the effect of the R2R gravure printing and drying process on the nanomorphology and nanostructure of the photoactive P3HT:PCBM thin films printed on PEDOT:PSS electrodes towards the fabrication of indium tin oxide (ITO)-free flexible OPVs. In order to achieve this, P3HT:PCBM blends of different concentration were R2R printed under various speeds on the PEDOT:PSS layers. Due to the limited drying time during the rolling, an amount of solvent remains in the P3HT:PCBM films and the slow-drying process takes place which leads to the vertical and lateral phase separation, according to the Spectroscopic Ellipsometry and Atomic Force Microscopy analysis. The enhanced slow-drying leads to stronger phase separation, larger P3HT crystallites according to the Grazing Incidence X-Ray Diffraction data and to weaker mechanical response as it was shown by the nanoindentation creep. However, in the surface of the films the P3HT crystallization is controlled by the impinged hot air during the drying, where the more the drying time the larger the surface P3HT crystallites. The integration of the printed P3HT:PCBM and PEDOT:PSS layers in an OPV device underlined the feasibility of fabricating ITO-free flexible OPVs by R2R gravure processes. © 2013 Elsevier B.V.

Dense active appearance models using a bounded diameter minimum spanning tree

We present a method for producing dense Active Appearance Models (AAMs), suitable for video-realistic synthesis. To this end we estimate a joint alignment of all training images using a set of pairwise registrations and ensure that these pairwise registrations are only calculated between similar images. This is achieved by defining a graph on the image set whose edge weights correspond to registration errors and computing a bounded diameter minimum spanning tree (BDMST). Dense optical flow is used to compute pairwise registration and we introduce a flow refinement method to align small scale texture. Once registration between training images has been established we propose a method to add vertices to the AAM in a way that minimises error between the observed flow fields and a flow field interpolated between the AAM mesh points. We demonstrate a significant improvement in model compactness using the proposed method and show it dealing with cases that are problematic for current state-of-the-art approaches.

Parameters influencing the maximum controllable current in gate commutated thyristors

The model of interconnected numerical device segments can give a prediction on the dynamic performance of large area full wafer devices such as the Gate Commutated Thyristors (GCTs) and can be used as an optimisation tool for designing GCTs. In this study the authors evaluate the relative importance of the shallow p-base thickness, its peak concentration, the depth of the p-base and the buffer peak concentration. © The Institution of Engineering and Technology 2014.