Biologically Based Artificial Navigation Systems: Review and Prospects

Trullier, Olivier; Wiener, Sidney I.; Berthoz, Alain; Meyer, Jean-Arcady

doi:10.1016/s0301-0082(96)00060-3

Cited by 331 publications

(321 citation statements)

References 130 publications

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“…Similarly, most navigation researchers accept the hypothesis that there are multiple navigation systems in the brain [150,173]. Interestingly, the division made in memory (into declarati6e and procedural systems) [33,35,120,211] parallels very closely the division made in navigation (into locale and taxon systems) [150,173,226]. In memory, declarative strategies are learned quickly, allow extensive flexibility, and involve the hippocampus [33,104,120], while procedural strategies are learned slowly, are inflexible, and involve the basal ganglia [91,120,192].…”

Section: Resultsmentioning

confidence: 99%

The hippocampal debate: are we asking the right questions?

Redish

2001

Behavioural Brain Research

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For years, the debate has been: 'Is the hippocampus the cognitive map?' or 'Is the hippocampus the core of memory?' These two hypotheses derived their original power from two key experiments-the cognitive map theory from the remarkable spatial correlates seen in recordings of hippocampal pyramidal cells and the memory theory from the profound amnesias seen in the patient H.M. Both of these key experiments have been reinterpreted over the years: hippocampal cells are correlated with much more than place and H.M. is missing much more than just his hippocampus. However, both theories are still debated today. The hippocampus clearly plays a role in both navigation and memory processing. The question that must be addressed is rather: 'What is the role played by the hippocampus in the navigation and memory systems?' By looking at the navigation system as a whole, one can identify the major role played by the hippocampus as correcting for accumulation errors that occur within idiothetic navigation systems. This is most clearly experimentally evident as reorientation when an animal is lost. Carrying this over to a more general process, this becomes a role of recalling a context, bridging a contextual gap, or, in other words, it becomes a form of recognition memory. I will review recent experimental data which seems to support this theory over the more general spatial or memory theories traditionally applied to hippocampus.

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Section: Resultsmentioning

confidence: 99%

The hippocampal debate: are we asking the right questions?

Redish

2001

Behavioural Brain Research

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“…Readers interested in theoretical and simulation models as well as in models of different types of navigation are referred to reviews of Trullier et al [19] and Franz and Mallot [1]. Recce and Harris [20] modeled the hippocampus as an auto-associative memory which stored a scene representation consisting of the bearings and distances of the surrounding landmarks and of a goal location.…”

Section: Previous Modelsmentioning

confidence: 99%

Spatial Representation and Navigation in a Bio-inspired Robot

Sheynikhovich

Chavarriaga

Strösslin

et al. 2005

Biomimetic Neural Learning for Intelligent Robots

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Abstract.A biologically inspired computational model of rodent representation-based (locale) navigation is presented. The model combines visual input in the form of realistic two dimensional grey-scale images and odometer signals to drive the firing of simulated place and head direction cells via Hebbian synapses. The space representation is built incrementally and on-line without any prior information about the environment and consists of a large population of location-sensitive units (place cells) with overlapping receptive fields. Goal navigation is performed using reinforcement learning in continuous state and action spaces, where the state space is represented by population activity of the place cells. The model is able to reproduce a number of behavioral and neurophysiological data on rodents. Performance of the model was tested on both simulated and real mobile Khepera robots in a set of behavioral tasks and is comparable to the performance of animals in similar tasks.

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“…Some graph models ignore this already available information and instead assume that a navigator stores raw or only barely processed sensory data ( [4], [20]). As a final point, actions themselves ( [19], [20], [45]) can not be sufficient to explain route knowledge. Rats can swim a route learned by walking [18].…”

Section: Problems With Graph Representations and Cognitive Mapsmentioning

confidence: 99%

“…In graphs the environment is represented as multiple interconnected units (e.g., [4], [19], [20], [45], [48]; see Fig. 1).…”

Section: Graph Representations and Cognitive Mapsmentioning

confidence: 99%

The Network of Reference Frames Theory: A Synthesis of Graphs and Cognitive Maps

Meilinger

Lecture Notes in Computer Science

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Abstract. The network of reference frames theory explains the orientation behavior of human and non-human animals in directly experienced environmental spaces, such as buildings or towns. This includes selflocalization, route and survey navigation. It is a synthesis of graph representations and cognitive maps, and solves the problems associated with explaining orientation behavior based either on graphs, maps or both of them in parallel. Additionally, the theory points out the unique role of vista spaces and asymmetries in spatial memory. New predictions are derived from the theory, one of which has been tested recently.

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Biologically Based Artificial Navigation Systems: Review and Prospects

Cited by 331 publications

References 130 publications

The hippocampal debate: are we asking the right questions?

The hippocampal debate: are we asking the right questions?

Spatial Representation and Navigation in a Bio-inspired Robot

The Network of Reference Frames Theory: A Synthesis of Graphs and Cognitive Maps

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