Comparative Experimental Studies on Spatial Memory and Learning in Rats and Robots

被引:18
作者
Barrera, Alejandra [1 ]
Caceres, Alejandra [2 ]
Weitzenfeld, Alfredo [1 ]
Ramirez-Amaya, Victor [2 ]
机构
[1] ITAM, Dept Comp Engn, Robot & Biorobot Labs, Mexico City 01080, DF, Mexico
[2] UNAM, Inst Neurobiol, Plast Neural Networks Lab, Queretaro 76230, Mexico
关键词
Hippocampus; Striatum; IEG Arc expression; Spatial learning; Cognitive map; Place recognition; Biorobotics; IMMEDIATE-EARLY GENE; COGNITIVE MAPS; PLACE CELLS; PATH-INTEGRATION; NAVIGATION; MODEL; ARC; REPRESENTATION; INVOLVEMENT; EXPRESSION;
D O I
10.1007/s10846-010-9467-y
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The study of behavioral and neurophysiological mechanisms involved in rat spatial cognition provides a basis for the development of computational models and robotic experimentation of goal-oriented learning tasks. These models and robotics architectures offer neurobiologists and neuroethologists alternative platforms to study, analyze and predict spatial cognition based behaviors. In this paper we present a comparative analysis of spatial cognition in rats and robots by contrasting similar goal-oriented tasks in a cyclical maze, where studies in rat spatial cognition are used to develop computational system-level models of hippocampus and striatum integrating kinesthetic and visual information to produce a cognitive map of the environment and drive robot experimentation. During training, Hebbian learning and reinforcement learning, in the form of Actor-Critic architecture, enable robots to learn the optimal route leading to a goal from a designated fixed location in the maze. During testing, robots exploit maximum expectations of reward stored within the previously acquired cognitive map to reach the goal from different starting positions. A detailed discussion of comparative experiments in rats and robots is presented contrasting learning latency while characterizing behavioral procedures during navigation such as errors associated with the selection of a non-optimal route, body rotations, normalized length of the traveled path, and hesitations. Additionally, we present results from evaluating neural activity in rats through detection of the immediate early gene Arc to verify the engagement of hippocampus and striatum in information processing while solving the cyclical maze task, such as robots use our corresponding models of those neural structures.
引用
收藏
页码:361 / 397
页数:37
相关论文
共 53 条
[1]  
[Anonymous], PRINCIPLES ANIMAL CO
[2]  
[Anonymous], P 15 MED C CONTR AUT
[3]  
[Anonymous], AN AN 7 P 7 INT C SI
[4]  
Arkin R.C., 1998, Behavior-based robotics
[5]   Spatial cognition and neuro-mimetic navigation: a model of hippocampal place cell activity [J].
Arleo, A ;
Gerstner, W .
BIOLOGICAL CYBERNETICS, 2000, 83 (03) :287-299
[6]   Cognitive navigation based on nonuniform gabor space sampling, unsupervised growing networks, and reinforcement learning [J].
Arleo, A ;
Smeraldi, F ;
Gerstner, W .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2004, 15 (03) :639-652
[7]   Biologically-inspired robot spatial cognition based on rat neurophysiological studies [J].
Barrera, Alejandra ;
Weitzenfeld, Alfredo .
AUTONOMOUS ROBOTS, 2008, 25 (1-2) :147-169
[8]  
Barto A. G., 1995, Models of Information Processing in the Basal Ganglia, P215
[9]   SIMULATION OF SPATIAL-LEARNING IN THE MORRIS WATER MAZE BY A NEURAL-NETWORK MODEL OF THE HIPPOCAMPAL-FORMATION AND NUCLEUS-ACCUMBENS [J].
BROWN, MA ;
SHARP, PE .
HIPPOCAMPUS, 1995, 5 (03) :171-188
[10]   A MODEL OF HIPPOCAMPAL FUNCTION [J].
BURGESS, N ;
RECCE, M ;
OKEEFE, J .
NEURAL NETWORKS, 1994, 7 (6-7) :1065-1081