Affordances. Motivations, and the World Graph Theory

Abstract

O' Keefe and Nadel (1978) distinguish two paradigms for navigation, the "locale system" for map-based navigation and the "taxon (behavioral orientation) system" for route navigation. This article models the taxon system, the map-based system, and their interaction, and argues that the map-based system involves the interaction of hippocampus and other systems.We relate taxes to the notion of an affordance. Just as a rat may have basic taxes for approaching food or avoiding a bright light, so does it have a wider repertoire of affordances for possible actions associated with immediate sensing of its environment. We propose that affordances are extracted by the rat posterior parietal cortex, which guides action selection by the premotor cortex and is influenced also by hypothalamic drive information.The taxon-affordances model (TAM) for taxon-based determination of movement direction is based on models of frog detour behavior, with expectations of future reward implemented using reinforcement learning. The specification of the direction of movement is refined by current affordances and motivational information to yield an appropriate course of action.The world graph (WG) theory expands the idea of a map by developing the hypothesis that cognitive and motivational states interact. This article describes an implementation of this theory, the WG model. The integrated TAM-WG model then allows us to explain data on the behavior of rats with and without fornix lesions, which disconnect the hippocampus from other neural systems.

Path planning versus cue responding: a bio-inspired model of switching between navigation strategies

“…Several models of strategy switching based on the theory of parallel memory systems were proposed earlier (Guazzelli et al 1998;Daw et al 2005;Girard et al 2005;Chavarriaga et al 2005). In the model of Guazzelli et al (1998), the orientations proposed by egocentric taxon and allocentric planning strategies are, respectively, determined by current affordances and cognitive knowledge.…”

“…In the model of Guazzelli et al (1998), the orientations proposed by egocentric taxon and allocentric planning strategies are, respectively, determined by current affordances and cognitive knowledge. The final movement is computed as a sum of these orientations that hand-tuned parameters adapt to the situation.…”

“…The first one is that these strategies are mediated by separate memory systems that can learn independently and in parallel (as in the computational models of, e.g., Guazzelli et al 1998;Girard et al 2005;Chavarriaga et al 2005;Daw et al 2005). The second assumption is that learning algorithms within the two memory systems are of different types: while response-based strategy relies on a slow and stereotyped "trial-and-error" learning implemented as a temporal-difference (TD) learning procedure, learning in the place-based strategy is fast and flexible and is based on a graph-search algorithm for finding a goal (as in Guazzelli et al 1998;Girard et al 2005;Daw et al 2005). The third assumption is that the selection mechanism is not fixed but continuously updates its estimates of the relative "goodness" of different strategies (as in Chavarriaga et al 2005;Daw et al 2005).…”

From visual affordances in monkey parietal cortex to hippocampo–parietal interactions underlying rat navigation

“…By contrast, the following model of the role of the parietal cortex and hippocampus of the rat in navigation is conceptual. A simulation study of parts of the model is provided by Guazzelli et al (1998). It addresses data from rat neurophysiology, but is strongly motivated by data from primate neurophysiology whose implications for analogous properties of the rat brain have yet to be tested.…”

Analyzing Interactions between Navigation Strategies Using a Computational Model of Action Selection

“…Besides, better understanding of these interactions in animals by use of the modelling approach described in this paper also contributes to the improvement of autonomous robot navigation systems. Indeed, several bioinspired studies began exploring the robotic use of multiple navigation strategies [12,[24][25][26], the topic is however far from being fully explored yet. leo, Karim Benchenane, Jean-Arcady Meyer and Denis Sheynikhovich for useful discussions.…”