Parallel and Interrelated Neural Systems Underlying Adaptive Navigation1
نویسندگان
چکیده
SYNOPSIS. The ability to process in parallel multiple forms of sensory information, and link sensory-sensory associations to behavior, presumably allows for the opportunistic use of the most reliable and predictive sensory modalities in diverse behavioral contexts. Evolutionary considerations indicate that such processing may represent a fundamental operating principle underlying complex sensory associations and sensorymotor integration. Here, we suggest that animal navigation is a particularly useful model of such opportunistic use of sensory and motor information because it is possible to study directly the effects of memory on neural system functions. First, comparative evidence for parallel processing across multiple brain structures during navigation is provided from the literatures on fish and rodent navigation. Then, based on neurophysiological evidence of coordinated, multiregional processing, we provide a neurobiological explanation of learning and memory effects on neural circuitry mediating navigation.
منابع مشابه
Adaptive Leader-Following and Leaderless Consensus of a Class of Nonlinear Systems Using Neural Networks
This paper deals with leader-following and leaderless consensus problems of high-order multi-input/multi-output (MIMO) multi-agent systems with unknown nonlinear dynamics in the presence of uncertain external disturbances. The agents may have different dynamics and communicate together under a directed graph. A distributed adaptive method is designed for both cases. The structures of the contro...
متن کاملParallel and interrelated neural systems underlying adaptive navigation.
The ability to process in parallel multiple forms of sensory information, and link sensory-sensory associations to behavior, presumably allows for the opportunistic use of the most reliable and predictive sensory modalities in diverse behavioral contexts. Evolutionary considerations indicate that such processing may represent a fundamental operating principle underlying complex sensory associat...
متن کاملAdaptive Neural Network Method for Consensus Tracking of High-Order Mimo Nonlinear Multi-Agent Systems
This paper is concerned with the consensus tracking problem of high order MIMO nonlinear multi-agent systems. The agents must follow a leader node in presence of unknown dynamics and uncertain external disturbances. The communication network topology of agents is assumed to be a fixed undirected graph. A distributed adaptive control method is proposed to solve the consensus problem utilizing re...
متن کاملAdaptive neural control of nonlinear fractional order multi- agent systems in the presence of error constraintion
In this paper, the problem of fractional order multi-agent tracking control problem is considered. External disturbances, uncertainties, error constraints, transient response suitability and desirable response tracking problems are the challenges in this study. Because of these problems and challenges, an adaptive control and neural estimator approaches are used in this study. In the first part...
متن کاملINTEGRATED ADAPTIVE FUZZY CLUSTERING (IAFC) NEURAL NETWORKS USING FUZZY LEARNING RULES
The proposed IAFC neural networks have both stability and plasticity because theyuse a control structure similar to that of the ART-1(Adaptive Resonance Theory) neural network.The unsupervised IAFC neural network is the unsupervised neural network which uses the fuzzyleaky learning rule. This fuzzy leaky learning rule controls the updating amounts by fuzzymembership values. The supervised IAFC ...
متن کامل