Topic
Representation (systemics)
About: Representation (systemics) is a research topic. Over the lifetime, 33821 publications have been published within this topic receiving 475461 citations.
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TL;DR: Experimental evidence is presented supporting the hypothesis that the functional role of gamma oscillations is not restricted to object representation established through bottom-up mechanisms of feature binding, but also extends to the cases of internally driven representations and to the maintenance of information in memory.
269 citations
TL;DR: In this article, a representation of decision-making in principle consistent with behavioural evidence is proposed, and the endogenous emergence of "innovations" in the forms of unexpected events and novel behaviours is also examined.
Abstract: Different sources of uncertainty are analysed and a representation of decision-making in principle consistent with behavioural evidence is proposed. The endogenous emergence of “innovations”, in the forms of unexpected events and novel behaviours is also examined.
265 citations
TL;DR: Undergraduate students may benefit more from learning mathematics through a single abstract, symbolic representation than from learning multiple concrete examples.
Abstract: Undergraduate students may benefit more from learning mathematics through a single abstract, symbolic representation than from learning multiple concrete examples.
263 citations
01 May 2007
TL;DR: A hierarchical probabilistic representation of space that is based on objects, a global topological representation of places with object graphs serving as local maps is proposed and the first efforts towards conceptualizing space on the basis of the human compatible representation so formed are details.
Abstract: Robots are rapidly evolving from factory work-horses to robot-companions. The future of robots, as our companions, is highly dependent on their abilities to understand, interpret and represent the environment in an efficient and consistent fashion, in a way that is comprehensible to humans. The work presented here is oriented in this direction. It suggests a hierarchical probabilistic representation of space that is based on objects. A global topological representation of places with object graphs serving as local maps is proposed. The work also details the first efforts towards conceptualizing space on the basis of the human compatible representation so formed. Such a representation and the resulting conceptualization would be useful for enabling robots to be cognizant of their surroundings. Experiments on place classification and place recognition are reported in order to demonstrate the applicability of such a representation towards understanding space and thereby performing spatial cognition. Further, relevant results from user studies validating the proposed representation are also reported. Thus, the theme of the work is - representation for spatial cognition.
262 citations
TL;DR: It is shown that the human hippocampal–entorhinal system can represent relationships between objects using a metric that depends on associative strength, akin to the successor representation that has been proposed to account for place and grid-cell firing patterns.
Abstract: The hippocampal-entorhinal system encodes a map of space that guides spatial navigation. Goal-directed behaviour outside of spatial navigation similarly requires a representation of abstract forms of relational knowledge. This information relies on the same neural system, but it is not known whether the organisational principles governing continuous maps may extend to the implicit encoding of discrete, non-spatial graphs. Here, we show that the human hippocampal-entorhinal system can represent relationships between objects using a metric that depends on associative strength. We reconstruct a map-like knowledge structure directly from a hippocampal-entorhinal functional magnetic resonance imaging adaptation signal in a situation where relationships are non-spatial rather than spatial, discrete rather than continuous, and unavailable to conscious awareness. Notably, the measure that best predicted a behavioural signature of implicit knowledge and blood oxygen level-dependent adaptation was a weighted sum of future states, akin to the successor representation that has been proposed to account for place and grid-cell firing patterns.
262 citations