Modelling the insect Mushroom Bodies: Application to sequence learning

被引：11

作者：

Arena, Paolo ^{[1
,2
]}

Cali, Marco ^{[1
]}

Patane, Luca ^{[1
]}

Portera, Agnese ^{[1
]}

Strauss, Roland ^{[3
]}

机构：

[1] Univ Catania, Dipartimento Ingn Elettr Elettron & Informat, I-95124 Catania, Italy

[2] INBB, I-00136 Rome, Italy

[3] Johannes Gutenberg Univ Mainz, Inst Zool Neurobiol 3, Mainz, Germany

来源：

NEURAL NETWORKS | 2015年 / 67卷

关键词：

Neuroscience; Insect brain; Insect Mushroom Bodies; Spiking neurons; Learning; Neural model; Context; NEURAL MODEL; FRUIT-FLY; PATTERNS; ARCHITECTURE; CEREBELLUM; BODY;

D O I：

10.1016/j.neunet.2015.03.006

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Learning and reproducing temporal sequences is a fundamental ability used by living beings to adapt behaviour repertoire to environmental constraints. This paper is focused on the description of a model based on spiking neurons, able to learn and autonomously generate a sequence of events. The neural architecture is inspired by the insect Mushroom Bodies (MBs) that are a crucial centre for multimodal sensory integration and behaviour modulation. The sequence learning capability coexists, within the insect brain computational model, with all the other features already addressed like attention, expectation, learning classification and others. This is a clear example that a unique neural structure is able to cope concurrently with a plethora of behaviours. Simulation results and robotic experiments are reported and discussed. (C) 2015 Elsevier Ltd. All rights reserved.

引用

页码：37 / 53

页数：17

共 53 条

[21] Use of Spatial Information and Search Strategies in a Water Maze Analog in Drosophila melanogaster [J].