On symmetries of crystals with defects related to a class of solvable groups (S2)

We find the geometrical symmetries of discrete structures which generalize the perfect lattices of crystallography to account for the existence of continuous distributions of defects

Geometrical issues in the continuum mechanics of solid crystals

We shall outline geometrical and algebraic ideas which appear to lie at the foundation of the theory of defective crystals that was introduced by Davini [5] in 1986. The focus of the paper will be on the connection between continuous and discrete models of such crystals, approached by consideration of the symmetries inherent in these models. To begin with, we review briefy the results of analysis of variational problems where relevant functionals have the symmetry of perfect (as opposed to defective) crystals, in order to motivate the subsequent study of symmetry in the case when defects are present. In the body of the paper we indicate how the theory of Lie groups, and their discrete subgroups, relates to this geometrical theory of defects, and discuss types of symmetry that occur

Mathematical frameworks for oscillatory network dynamics in neuroscience

The tools of weakly coupled phase oscillator theory have had a profound impact on the neuroscience community, providing insight into a variety of network behaviours ranging from central pattern generation to synchronisation, as well as predicting novel network states such as chimeras. However, there are many instances where this theory is expected to break down, say in the presence of strong coupling, or must be carefully interpreted, as in the presence of stochastic forcing. There are also surprises in the dynamical complexity of the attractors that can robustly appear—for example, heteroclinic network attractors. In this review we present a set of mathemat- ical tools that are suitable for addressing the dynamics of oscillatory neural networks, broadening from a standard phase oscillator perspective to provide a practical frame- work for further successful applications of mathematics to understanding network dynamics in neuroscience

Geometrical issues in the continuum mechanics of solid crystals

We shall outline geometrical and algebraic ideas which appear to lie at the foundation of the theory of defective crystals that was introduced by Davini [5] in 1986. The focus of the paper will be on the connection between continuous and discrete models of such crystals, approached by consideration of the symmetries inherent in these models. To begin with, we review briefy the results of analysis of variational problems where relevant functionals have the symmetry of perfect (as opposed to defective) crystals, in order to motivate the subsequent study of symmetry in the case when defects are present. In the body of the paper we indicate how the theory of Lie groups, and their discrete subgroups, relates to this geometrical theory of defects, and discuss types of symmetry that occur

A brain-wave equation incorporating axo-dendritic connectivity

We introduce an integral model of a two-dimensional neural field that includes a third dimension representing space along a dendritic tree that can incorporate realistic patterns of axo-dendritic connectivity. For natural choices of this connectivity we show how to construct an equivalent brainwave partial differential equation that allows for effcient numerical simulation of the model. This is used to highlight the effects that passive dendritic properties can have on the speed and shape of large scale traveling cortical waves

Clusters in nonsmooth oscillator networks

For coupled oscillator networks with Laplacian coupling the master stability function (MSF) has proven a particularly powerful tool for assessing the stability of the synchronous state. Using tools from group theory this approach has recently been extended to treat more general cluster states. However, the MSF and its generalisations require the determination of a set of Floquet multipliers from variational equations obtained by linearisation around a periodic orbit. Since closed form solutions for periodic orbits are invariably hard to come by the framework is often explored using numerical techniques. Here we show that further insight into network dynamics can be obtained by focusing on piecewise linear (PWL) oscillator models. Not only do these allow for the explicit construction of periodic orbits, their variational analysis can also be explicitly performed. The price for adopting such nonsmooth systems is that many of the notions from smooth dynamical systems, and in particular linear stability, need to be modified to take into account possible jumps in the components of Jacobians. This is naturally accommodated with the use of \textit{saltation} matrices. By augmenting the variational approach for studying smooth dynamical systems with such matrices we show that, for a wide variety of networks that have been used as models of biological systems, cluster states can be explicitly investigated. By way of illustration we analyse an integrate-and-fire network model with event-driven synaptic coupling as well as a diffusively coupled network built from planar PWL nodes, including a reduction of the popular Morris--Lecar neuron model. We use these examples to emphasise that the stability of network cluster states can depend as much on the choice of single node dynamics as it does on the form of network structural connectivity. Importantly the procedure that we present here, for understanding cluster synchronisation in networks, is valid for a wide variety of systems in biology, physics, and engineering that can be described by PWL oscillators

Geometrical issues in the continuum mechanics of solid crystals

We shall outline geometrical and algebraic ideas which appear to lie at the foundation of the theory of defective crystals that was introduced by Davini [5] in 1986. The focus of the paper will be on the connection between continuous and discrete models of such crystals, approached by consideration of the symmetries inherent in these models. To begin with, we review briefy the results of analysis of variational problems where relevant functionals have the symmetry of perfect (as opposed to defective) crystals, in order to motivate the subsequent study of symmetry in the case when defects are present. In the body of the paper we indicate how the theory of Lie groups, and their discrete subgroups, relates to this geometrical theory of defects, and discuss types of symmetry that occur

A classification of the symmetries of uniform discrete defective crystals

Crystals which have a uniform distribution of defects are endowed with a Lie group description which allows one to construct an associated discrete structure. These structures are in fact the discrete subgroups of the ambient Lie group. The geometrical symmetries of these structures can be computed in terms of the changes of generators of the discrete subgroup which preserve the discrete set of points. Here a classification of the symmetries for the discrete subgroups of a particular class of three-dimensional solvable Lie group is presented. It is a fact that there are only three mathematically distinct types of Lie groups which model uniform defective crystals, and the calculations given here complete the discussion of the symmetries of the corresponding discrete structures. We show that those symmetries corresponding to automorphisms of the discrete subgroups extend uniquely to symmetries of the ambient Lie group and we regard these symmetries as (restrictions of) elastic deformations of the continuous defective crystal. Other symmetries of the discrete structures are classified as ‘inelastic’ symmetries

Mean-Field Models for EEG/MEG: From Oscillations to Waves

Neural mass models have been used since the 1970s to model the coarse-grained activity of large populations of neurons. They have proven especially fruitful for understanding brain rhythms. However, although motivated by neurobiological considerations they are phenomenological in nature, and cannot hope to recreate some of the rich repertoire of responses seen in real neuronal tissue. Here we consider a simple spiking neuron network model that has recently been shown to admit an exact mean-field description for both synaptic and gap-junction interactions. The mean-field model takes a similar form to a standard neural mass model, with an additional dynamical equation to describe the evolution of within-population synchrony. As well as reviewing the origins of this next generation mass model we discuss its extension to describe an idealised spatially extended planar cortex. To emphasise the usefulness of this model for EEG/MEG modelling we show how it can be used to uncover the role of local gap-junction coupling in shaping large scale synaptic waves