0000000000430816

AUTHOR

Alessia Annibale

showing 3 related works from this author

Retrieving infinite numbers of patterns in a spin-glass model of immune networks

2013

The similarity between neural and immune networks has been known for decades, but so far we did not understand the mechanism that allows the immune system, unlike associative neural networks, to recall and execute a large number of memorized defense strategies {\em in parallel}. The explanation turns out to lie in the network topology. Neurons interact typically with a large number of other neurons, whereas interactions among lymphocytes in immune networks are very specific, and described by graphs with finite connectivity. In this paper we use replica techniques to solve a statistical mechanical immune network model with `coordinator branches' (T-cells) and `effector branches' (B-cells), a…

0301 basic medicineSimilarity (geometry)Spin glassComputer sciencestatistical mechanicFOS: Physical sciencesGeneral Physics and AstronomyNetwork topologyTopology01 natural sciencesQuantitative Biology::Cell Behavior03 medical and health sciencesCell Behavior (q-bio.CB)0103 physical sciencesattractor neural-networks; statistical mechanics; brain networks; Physics and Astronomy (all)Physics - Biological Physics010306 general physicsAssociative propertybrain networkArtificial neural networkMechanism (biology)ErgodicityDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksAcquired immune system030104 developmental biologyBiological Physics (physics.bio-ph)FOS: Biological sciencesattractor neural-networkQuantitative Biology - Cell Behavior
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Immune networks: Multi-tasking capabilities at medium load

2013

Associative network models featuring multi-tasking properties have been introduced recently and studied in the low load regime, where the number $P$ of simultaneously retrievable patterns scales with the number $N$ of nodes as $P\sim \log N$. In addition to their relevance in artificial intelligence, these models are increasingly important in immunology, where stored patterns represent strategies to fight pathogens and nodes represent lymphocyte clones. They allow us to understand the crucial ability of the immune system to respond simultaneously to multiple distinct antigen invasions. Here we develop further the statistical mechanical analysis of such systems, by studying the medium load r…

Statistics and ProbabilityModularity (networks)Theoretical computer scienceDegree (graph theory)Associative networkComputer scienceGeneral Physics and AstronomyFOS: Physical sciencesStatistical and Nonlinear PhysicsDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksModeling and SimulationFOS: Biological sciencesCell Behavior (q-bio.CB)Human multitaskingQuantitative Biology - Cell BehaviorRelevance (information retrieval)Cluster analysisImmune Network Statistical Mechanics Hopfield model Parallel RetrievalMathematical Physics
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Immune networks: multitasking capabilities near saturation

2013

Pattern-diluted associative networks were introduced recently as models for the immune system, with nodes representing T-lymphocytes and stored patterns representing signalling protocols between T- and B-lymphocytes. It was shown earlier that in the regime of extreme pattern dilution, a system with $N_T$ T-lymphocytes can manage a number $N_B!=!\order(N_T^\delta)$ of B-lymphocytes simultaneously, with $\delta!<!1$. Here we study this model in the extensive load regime $N_B!=!\alpha N_T$, with also a high degree of pattern dilution, in agreement with immunological findings. We use graph theory and statistical mechanical analysis based on replica methods to show that in the finite-connectivit…

Statistics and ProbabilityImmune Network Statistical Mechanics Hopfield Model Parallel RetrievalQuantitative Biology::Tissues and OrgansPhase (waves)FOS: Physical sciencesGeneral Physics and AstronomyInterference (wave propagation)TopologyQuantitative Biology::Cell BehaviorCell Behavior (q-bio.CB)Physics - Biological PhysicsFinite setMathematical PhysicsConnectivityAssociative propertyPhysicsDegree (graph theory)ReplicaStatistical and Nonlinear PhysicsGraph theoryDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksBiological Physics (physics.bio-ph)FOS: Biological sciencesModeling and SimulationQuantitative Biology - Cell BehaviorJournal of Physics A: Mathematical and Theoretical
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