893 research outputs found
Mammalian Brain As a Network of Networks
Acknowledgements AZ, SG and AL acknowledge support from the Russian Science Foundation (16-12-00077). Authors thank T. Kuznetsova for Fig. 6.Peer reviewedPublisher PD
NASA JSC neural network survey results
A survey of Artificial Neural Systems in support of NASA's (Johnson Space Center) Automatic Perception for Mission Planning and Flight Control Research Program was conducted. Several of the world's leading researchers contributed papers containing their most recent results on artificial neural systems. These papers were broken into categories and descriptive accounts of the results make up a large part of this report. Also included is material on sources of information on artificial neural systems such as books, technical reports, software tools, etc
Dynamical Analysis for High-Order Delayed Hopfield Neural Networks with Impulses
The global exponential stability and uniform stability of the equilibrium point for high-order delayed Hopfield neural networks with impulses are studied. By utilizing Lyapunov functional method, the quality of negative definite matrix, and the linear matrix inequality approach, some new stability criteria for such system are derived. The results are related to the size of delays and impulses. Two examples are also given to illustrate the effectiveness of our results
Dynamical Analysis of DTNN with Impulsive Effect
We present dynamical analysis of discrete-time delayed neural networks with impulsive effect. Under impulsive effect, we derive some new criteria for the invariance and attractivity of discretetime neural networks by using decomposition approach and delay difference inequalities. Our results improve or extend the existing ones
New Results for Periodic Solution of High-Order BAM Neural Networks with Continuously Distributed Delays and Impulses
By M-matrix theory, inequality techniques, and Lyapunov functional method, certain sufficient conditions are obtained to ensure the existence, uniqueness, and global exponential stability of periodic solution for a new type of high-order BAM neural networks with continuously distributed delays and impulses. These novel conditions extend and improve some previously known results in the literature. Finally, an illustrative example and its numerical simulation are given to show the feasibility and correctness of the derived criteria
Phase models and clustering in networks of oscillators with delayed coupling
We consider a general model for a network of oscillators with time delayed,
circulant coupling. We use the theory of weakly coupled oscillators to reduce
the system of delay differential equations to a phase model where the time
delay enters as a phase shift. We use the phase model to study the existence
and stability of cluster solutions. Cluster solutions are phase locked
solutions where the oscillators separate into groups. Oscillators within a
group are synchronized while those in different groups are phase-locked. We
give model independent existence and stability results for symmetric cluster
solutions. We show that the presence of the time delay can lead to the
coexistence of multiple stable clustering solutions. We apply our analytical
results to a network of Morris Lecar neurons and compare these results with
numerical continuation and simulation studies
Space, time and memory in the medial temporal lobe
This thesis focuses on memory and the representation of space in the medial temporal lobe, their interaction and their temporal structure.
Chapter 1 briefly introduces the topic, with emphasis on the open questions that the subsequent chapters aim to address.
Chapter 2 is dedicated to the issue of spatial memory in the medial entorhinal cortex.
It investigates the possibility to store multiple independent maps in a recurrent network of grid cells, from a theoretical perspective. This work was conducted in collaboration with Remi Monasson, Alexis Dubreuil and Sophie Rosay and is published in (Spalla et al. 2019).
Chapter 3 focuses on the problem of the dynamical update of the representation of space during navigation.
It presents the results of the analysis of electrophysiological data, previously collected by Charlotte Boccara (Boccara et al., 2010), investigating the encoding of self-movement signals (speed and angular velocity of the head) in the parahippocampal region of rats.
Chapter 4 addresses the problem of the temporal dynamics of memory retrieval, again from a computational point of view. A continuous attractor network model is presented, endowed with a mechanism that makes it able to retrieve continuous temporal sequences. The dynamical behaviour of the system is investigated with analytical calculations and numerical simulations, and the storage capacity for dynamical memories is computed.
Finally, chapter 4 discusses the meaning and the scope of the results presented, and highlights possible future directions
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