A mathematical analysis of the effects of Hebbian learning rules on the dynamics and structure of discrete-time random recurrent neural networks

We present a mathematical analysis of the effects of Hebbian learning in random recurrent neural networks, with a generic Hebbian learning rule including passive forgetting and different time scales for neuronal activity and learning dynamics. Previous numerical works have reported that Hebbian learning drives the system from chaos to a steady state through a sequence of bifurcations. Here, we interpret these results mathematically and show that these effects, involving a complex coupling between neuronal dynamics and synaptic graph structure, can be analyzed using Jacobian matrices, which introduce both a structural and a dynamical point of view on the neural network evolution. Furthermore, we show that the sensitivity to a learned pattern is maximal when the largest Lyapunov exponent is close to 0. We discuss how neural networks may take advantage of this regime of high functional interest

Information System: Transport Dynamic Cartography in Alsace.

International audienceThe issue of the presented work is to publish on line a dynamic cartography system of the transport traffic evaluation, based upon the Alsace (France) regional level experiment. After a large design work of a transport database, arose questions about accessibility, data updating, choice of information processing systems, and development of Internet tools. Three points of view will be approached: the system design from the user point of view, the raised questions of communication and the data-processing. The synthesis allows analyzing the experiment of the installation of a Catalyse tool at a public State level service, at a French "région" level

Questioning the rise of gelatinous zooplankton in the World's oceans

During the past several decades, high numbers of gelatinous zooplankton species have been reported in many estuarine and coastal ecosystems. Coupled with media-driven public perception, a paradigm has evolved in which the global ocean ecosystems are thought to be heading toward being dominated by “nuisance” jellyfish. We question this current paradigm by presenting a broad overview of gelatinous zooplankton in a historicalcontext to develop the hypothesis that population changes reflect the human-mediated alteration of global ocean ecosystems. To this end, we synthesize information related to the evolutionary context of contemporary gelatinous zooplankton blooms, the human frame of reference forchanges in gelatinous zooplankton populations, and whether sufficient data are available to have established the paradigm. We conclude that the current paradigm in which it is believed that there has been a global increase in gelatinous zooplankton is unsubstantiated, and we develop a strategy for addressing the critical questions about long-term, human-related changes in the sea as they relate to gelatinous zooplankton blooms

A Predictive Coding Account for Chaotic Itinerancy

As a phenomenon in dynamical systems allowing autonomous switching between stable behaviors, chaotic itinerancy has gained interest in neurorobotics research. In this study, we draw a connection between this phenomenon and the predictive coding theory by showing how a recurrent neural network implementing predictive coding can generate neural trajectories similar to chaotic itinerancy in the presence of input noise. We propose two scenarios generating random and past-independent attractor switching trajectories using our model

Neurobiologically Inspired Mobile Robot Navigation and Planning

After a short review of biologically inspired navigation architectures, mainly relying on modeling the hippocampal anatomy, or at least some of its functions, we present a navigation and planning model for mobile robots. This architecture is based on a model of the hippocampal and prefrontal interactions. In particular, the system relies on the definition of a new cell type “transition cells” that encompasses traditional “place cells”

Emergence and long-term maintenance of modularity in plastic networks of spiking neurons

In the last three decades it has become clear that cortical regions, interconnected via white-matter fibers, form a modular and hierarchical network. This organization, which has also been seen at the microscopic level in the form of interconnected neural assemblies, is believed to support the coexistence of segregation (specialization) and integration (binding) of information. A fundamental open question is to understand how this complex structure can emerge in the brain. Here, we made a first step to address this question and propose that adaptation to various inputs could be the key driving mechanism for the formation of structural assemblies. To test this idea, we develop a model of quadratic integrate-and-fire spiking neurons, trained to stimuli targetting distinct sub-populations. The model is designed to satisfy several biologically plausible constraints: (i) the network contains excitatory and inhibitory neurons with Hebbian and anti-Hebbian STDP; and (ii) neither the neuronal activity nor the synaptic weights are frozen after the learning phase. Instead, the network continues firing spontaneously while synaptic plasticity remains active. We find that only the combination of the two inhibitory STDP sub-populations allows for the formation of stable modular organization in the network, with each sub-population playing a distinct role. The Hebbian sub-population controls for the firing rate and the anti-Hebbian mediates pattern selectivity. After the learning phase, the network activity settles into an asynchronous irregular resting-state, resembling the behaviour typically observed in-vivo in the cortex. This post-learning activity also displays spontaneous memory recalls, which are fundamental for the long-term consolidation of the learned memory items. The model introduced represents a starting point for the joint investigation of neural dynamics, connectivity and plasticity.Comment: 28 pages, 11 figure

Phylogenetic relationships of the north-eastern Atlantic and Mediterranean blenniids

The phylogenetic relationships of 27 north-eastern Atlantic and Mediterranean blennioids are analysed based on a total of 1001 bp from a combined fragment of the 12S and 16S mitochondrial rDNA. The most relevant results with implications in current blenniid taxonomy are: (1) Lipophrys pholis and Lipophrys (= Paralipophrys) trigloides are included in a well-supported clade that by the rule of precedence must be named Lipophrys; (2) the sister species of this clade are not the remaining species of the genus Lipophrys but instead a monotypic genus comprising Cory-phoblennius galerita; (3) the smaller species of Lipophrys were recovered in another well-supported and independent clade, which we propose to be recognized as Microlipophrys; (4) although some authors included the genera Salaria and Lipophrys in a single group we have never recovered such a relationship. Instead, Salaria is more closely related to the genera Scartella and Parablennius; (5) the genus Parablennius, which was never recovered as a monophyletic clade, is very diverse and may include several distinct lineages; (6) the relative position of Aidablennius sphynx casts some doubts on the currently recognized relationships between the different blenniid tribes. Meristic, morphological, behavioural and ecological characters support our results and are also discussed. The possible roles of the tropical West African coast and the Mediterranean in the diversification of blenniids are discussed. (c) 2005 The Linnean Society of London.info:eu-repo/semantics/publishedVersio

Truck silhouettes analysis with wim data on a63 motorway

Beyond enforcement of commercial truck weight regulations, weigh in motion (WIM) devices provide detailed data very useful to analyse road freight traffic characteristics. This item presents results on silhouette analysis on motorway. Detailed but anonymised data coming from A63 motorway WIM devices were provided by Cerema to Atlandes.Papers presented at the 40th International Southern African Transport Conference on 04 -08 July 202