5,299 research outputs found
Chimera states: Coexistence of coherence and incoherence in networks of coupled oscillators
A chimera state is a spatio-temporal pattern in a network of identical
coupled oscillators in which synchronous and asynchronous oscillation coexist.
This state of broken symmetry, which usually coexists with a stable spatially
symmetric state, has intrigued the nonlinear dynamics community since its
discovery in the early 2000s. Recent experiments have led to increasing
interest in the origin and dynamics of these states. Here we review the history
of research on chimera states and highlight major advances in understanding
their behaviour.Comment: 26 pages, 3 figure
Temporal structure of neural oscillations underlying sensorimotor coordination: a theoretical approach with evolutionary robotics
The temporal structure of neural oscillations has become a widespread hypothetical
\mechanism" to explain how neurodynamics give rise to neural functions. Despite the
great number of empirical experiments in neuroscience and mathematical and computa-
tional modelling investigating the temporal structure of the oscillations, there are still
few systematic studies proposing dynamical explanations of how it operates within closed
sensorimotor loops of agents performing minimally cognitive behaviours. In this thesis
we explore this problem by developing and analysing theoretical models of evolutionary
robotics controlled by oscillatory networks. The results obtained suggest that: i) the in-
formational content in an oscillatory network about the sensorimotor dynamics is equally
distributed throughout the entire range of phase relations; neither synchronous nor desyn-
chronous oscillations carries a privileged status in terms of informational content in relation
to an agent's sensorimotor activity; ii) although the phase relations of oscillations with
a narrow frequency difference carry a relatively higher causal relevance than the rest of
the phase relations to sensorimotor coordinations, overall there is no privileged functional
causal contribution to either synchronous or desynchronous oscillations; and iii) oscilla-
tory regimes underlying functional behaviours (e.g. phototaxis, categorical perception) are
generated and sustained by the agent's sensorimotor loop dynamics, they depend not only
on the dynamic structure of a sensory input but also on the coordinated coupling of the
agent's motor-sensory dynamics. This thesis also contributes to the Coordination Dynam-
ics framework (Kelso, 1995) by analysing the dynamics of the HKB (Haken-Kelso-Bunz)
equation within a closed sensorimotor loop and by discussing the theoretical implications
of such an analysis. Besides, it contributes to the ongoing philosophical debate about
whether actions are either causally relevant or a constituent of cognitive functionalities by
bringing this debate to the context of oscillatory neurodynamics and by illustrating the
constitutive notion of actions to cognition
Synchronisation effects on the behavioural performance and information dynamics of a simulated minimally cognitive robotic agent
Oscillatory activity is ubiquitous in nervous systems, with solid evidence that synchronisation mechanisms underpin cognitive processes. Nevertheless, its informational content and relationship with behaviour are still to be fully understood. In addition, cognitive systems cannot be properly appreciated without taking into account brain–body– environment interactions. In this paper, we developed a model based on the Kuramoto Model of coupled phase oscillators to explore the role of neural synchronisation in the performance of a simulated robotic agent in two different minimally cognitive tasks. We show that there is a statistically significant difference in performance and evolvability depending on the synchronisation regime of the network. In both tasks, a combination of information flow and dynamical analyses show that networks with a definite, but not too strong, propensity for synchronisation are more able to reconfigure, to organise themselves functionally and to adapt to different behavioural conditions. The results highlight the asymmetry of information flow and its behavioural correspondence. Importantly, it also shows that neural synchronisation dynamics, when suitably flexible and reconfigurable, can generate minimally cognitive embodied behaviour
Alternative model-building for the study of socially interactive robots
In this discussion paper, we consider the potential merits of applying an alternative approach to model building (Empirical Modelling, also known as EM) in studying social aspects of human-robot interaction (HRI). The first section of the paper considers issues in modelling for HRI. The second introduces EM principles, outlining their potential application to modelling for HRI and its implications. The final section examines the prospects for applying EM to HRI from a practical perspective with reference to a simple case study and to existing models
Modelling the influence of RKIP on the ERK signalling pathway using the stochastic process algebra PEPA
This paper examines the influence of the Raf Kinase Inhibitor Protein (RKIP) on the Extracellular signal Regulated Kinase (ERK) signalling pathway [5] through modelling in a Markovian process algebra, PEPA [11]. Two models of the system are presented, a reagent-centric view and a pathway-centric view. The models capture functionality at the level of subpathway, rather than at a molecular level. Each model affords a different perspective of the pathway and analysis. We demonstrate the two models to be formally equivalent using the timing-aware bisimulation defined over PEPA models and discuss the biological significance
Neuronal oscillations, information dynamics, and behaviour: an evolutionary robotics study
Oscillatory neural activity is closely related to cognition and behaviour, with synchronisation mechanisms playing a key role in the integration and functional organization of different cortical areas. Nevertheless, its informational content and relationship with behaviour - and hence cognition - are still to be fully understood.
This thesis is concerned with better understanding the role of neuronal oscillations and information dynamics towards the generation of embodied cognitive behaviours and with investigating the efficacy of such systems as practical robot controllers. To this end, we develop a novel model based on the Kuramoto model of coupled phase oscillators and perform three minimally cognitive evolutionary robotics experiments. The analyses focus both on a behavioural level description, investigating the robot’s trajectories, and on a mechanism level description, exploring the variables’ dynamics and the information transfer properties within and between the agent’s body and the environment.
The first experiment demonstrates that in an active categorical perception task under normal and inverted vision, networks with a definite, but not too strong, propensity for synchronisation are more able to reconfigure, to organise themselves functionally, and to adapt to different behavioural conditions. The second experiment relates assembly constitution and phase reorganisation dynamics to performance in supervised and unsupervised learning tasks. We demonstrate that assembly dynamics facilitate the evolutionary process, can account for varying degrees of stimuli modulation of the sensorimotor interactions, and can contribute to solving different tasks leaving aside other plasticity mechanisms. The third experiment explores an associative learning task considering a more realistic connectivity pattern between neurons. We demonstrate that networks with travelling waves as a default solution perform poorly compared to networks that are normally synchronised in the absence of stimuli.
Overall, this thesis shows that neural synchronisation dynamics, when suitably flexible and reconfigurable, produce an asymmetric flow of information and can generate minimally cognitive embodied behaviours
Effect of distributed energy systems on the electricity grid
A feasibility study is being carried out at Ecotricity into a distributed
energy storage system comprising Energy stores (batteries) placed at
consumer level (in customer’s homes). The aim is to flatten consumer
demand and make better use of home-based generation. The Study
Group considered the mechanism of connecting batteries to the local
distribution system, the ability to meet engineering requirements for the
standard of the connection, and the potential impact of large numbers of
such connections on stability of the local distribution network. Network
and (DC-AC) invertor models were used to examine network connection
transients. A statistical model was proposed to estimate the distribution
of key electrical parameters to determine the likelihood of engineering
standards being exceeded. The Study Group also considered stochastic
methods of modelling wind speed, to better understand the requirements
for battery energy storage as a complement to wind power
Theory of Interacting Neural Networks
In this contribution we give an overview over recent work on the theory of
interacting neural networks. The model is defined in Section 2. The typical
teacher/student scenario is considered in Section 3. A static teacher network
is presenting training examples for an adaptive student network. In the case of
multilayer networks, the student shows a transition from a symmetric state to
specialisation. Neural networks can also generate a time series. Training on
time series and predicting it are studied in Section 4. When a network is
trained on its own output, it is interacting with itself. Such a scenario has
implications on the theory of prediction algorithms, as discussed in Section 5.
When a system of networks is trained on its minority decisions, it may be
considered as a model for competition in closed markets, see Section 6. In
Section 7 we consider two mutually interacting networks. A novel phenomenon is
observed: synchronisation by mutual learning. In Section 8 it is shown, how
this phenomenon can be applied to cryptography: Generation of a secret key over
a public channel.Comment: Contribution to Networks, ed. by H.G. Schuster and S. Bornholdt, to
be published by Wiley VC
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