Code-specific policy gradient rules for spiking neurons

Although it is widely believed that reinforcement learning is a suitable tool for describing behavioral learning, the mechanisms by which it can be implemented in networks of spiking neurons are not fully understood. Here, we show that different learning rules emerge from a policy gradient approach depending on which features of the spike trains are assumed to influence the reward signals, i.e., depending on which neural code is in effect. We use the framework of Williams (1992) to derive learning rules for arbitrary neural codes. For illustration, we present policy-gradient rules for three different example codes - a spike count code, a spike timing code and the most general "full spike train" code - and test them on simple model problems. In addition to classical synaptic learning, we derive learning rules for intrinsic parameters that control the excitability of the neuron. The spike count learning rule has structural similarities with established Bienenstock-Cooper-Munro rules. If the distribution of the relevant spike train features belongs to the natural exponential family, the learning rules have a characteristic shape that raises interesting prediction problems.

Grain boundary interface mechanics in strain gradient crystal plasticity

Interactions between dislocations and grain boundaries play an important role in the plastic deformation of polycrystalline metals. Capturing accurately the behaviour of these internal interfaces is particularly important for applications where the relative grain boundary fraction is significant, such as ultra fine-grained metals, thin films and microdevices. Incorporating these micro-scale interactions (which are sensitive to a number of dislocation, interface and crystallographic parameters) within a macro-scale crystal plasticity model poses a challenge. The innovative features in the present paper include (i) the formulation of a thermodynamically consistent grain boundary interface model within a microstructurally motivated strain gradient crystal plasticity framework, (ii) the presence of intra-grain slip system coupling through a microstructurally derived internal stress, (iii) the incorporation of inter-grain slip system coupling via an interface energy accounting for both the magnitude and direction of contributions to the residual defect from all slip systems in the two neighbouring grains, and (iv) the numerical implementation of the grain boundary model to directly investigate the influence of the interface constitutive parameters on plastic deformation. The model problem of a bicrystal deforming in plane strain is analysed. The influence of dissipative and energetic interface hardening, grain misorientation, asymmetry in the grain orientations and the grain size are systematically investigated. In each case, the crystal response is compared with reference calculations with grain boundaries that are either 'microhard' (impenetrable to dislocations) or 'microfree' (an infinite dislocation sink). © 2013 Elsevier Ltd. All rights reserved.

Finite Element studies on indentation size effect using a higher order strain gradient theory

In this work, a Finite Element implementation of a higher order strain gradient theory (due to Fleck and Hutchinson, 2001) has been used within the framework of large deformation elasto-viscoplasticity to study the indentation of metals with indenters of various geometries. Of particular interest is the indentation size effect (ISE) commonly observed in experiments where the hardness of a range of materials is found to be significantly higher at small depths of indentation but reduce to a lower, constant value at larger depths. That the ISE can be explained by strain gradient plasticity is well known but this work aims to qualitatively compare a gamut of experimental observations on this effect with predictions from a higher order strain gradient theory. Results indicate that many of the experimental observations are qualitatively borne out by our simulations. However, areas exist where conflicting experimental results make assessment of numerical predictions difficult. © 2012 Elsevier Ltd. All rights reserved.

Scalar gradient behaviour in MILD combustion

The results of three-dimensional Direct Numerical Simulation (DNS) of Moderate, Intense Low-oxygen Dilution (MILD) and conventional premixed turbulent combustion conducted using a skeletal mechanism including the effects of non-unity Lewis numbers and temperature dependent transport properties are analysed to investigate combustion characteristics using scalar gradient information. The DNS data is also used to synthesise laser induced fluorescence (LIF) signals of OH, CH2O, and CHO. These signals are analysed to verify if they can be used to study turbulent MILD combustion and it has been observed that at least two (OH and CH2O) LIF signals are required since the OH increase across the reaction zone is smaller in MILD combustion compared to premixed combustion. The scalar gradient PDFs conditioned on the reaction rate obtained from the DNS data and synthesised LIF signals suggests a strong gradient in the direction normal to the MILD reaction zone with moderate reaction rate implying flamelet combustion. However, the PDF of the normal gradient is as broad as for the tangential gradient when the reaction rate is high. This suggests a non-flamelet behaviour, which is due to interaction of reaction zones. The analysis of the conditional PDFs for the premixed case confirms the expected behaviour of scalar gradient in flamelet combustion. It has been shown that the LIF signals synthesised using 2D slices of DNS data also provide very similar insights. These results demonstrate that the so-called flameless combustion is not an idealised homogeneous reactive mixture but has common features of conventional combustion while containing distinctive characteristics. © 2013 The Combustion Institute.