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This hybrid of review and personal essay argues that models of visual construction are essential to extend spatial navigation models to models that link episodic memory and imagination. The starting point is the TAM-WG model, combining the Taxon Affordance Model and the World Graph model of spatial navigation. The key here is to reject approaches in which memory is restricted to unanalyzed views from familiar places, and their later recall. Instead, we will seek mechanisms for imagining truly novel scenes and episodes. We thus introduce a specific variant of schema theory and VISIONS, a cooperative computation model of visual scene understanding in which a scene is represented by an assemblage of schema instances with links to lower-level "patches" of relevant visual data. We sketch a new conceptual framework for future modeling, Visual Integration of Diverse Multi-Modal Aspects, by extending VISIONS from static scenes to episodes combining agents, actions and objects and assess its relevance to both navigation and episodic memory. We can then analyze imagination as a constructive process that combines aspects of memories of prior episodes along with other schemas and adjusts them into a coherent whole which, through expectations associated with diverse episodes and schemas, may yield the linkage of episodes that constitutes a dream or a narrative. The result is IBSEN, a conceptual model of Imagination in Brain Systems for Episodes and Navigation. The essay closes by analyzing other papers in this Special Issue to assess to what extent their results relate to the research proposed here.

Based on an interference theory of forgetting in short-term memory (STM), we model STM by a network of neural limits with mutual inhibition. Sequences are acquired by combining a Hebbian learning rule and a normalization rule with sequential system activation. As long as sequences are acquired, they can be recognized without being affected by speeds in presentation. The model of sequence reproduction consists of two reciprocally connected networks, one of which behaves as sequence recognizers. Reproduction of complex sequences is shown to be able to maintain interval lengths of sequence components. A mechanism of degree self-tuning based on a global inhibitor is proposed for the model to optimally learn required context lengths in order to disambiguate associations in complex sequence reproduction.

It has been found behaviorally that visual habituation in toads exhibits locus specificity and partial stimulus specificity. Dishabituation among different configurations of visual worm stimuli forms an ordered hierarchy. This paper presents a computational model of the toad visual system involved in pattern discrimination, including retina, tectum, and anterior thalamus. In the model w e propose that the toad discriminates visual objects based on temporal responses, and anterior thalamus has differing representations of different stimulus configurations. This theory is developed through a large scale neural simulation. With a minimum number of hypotheses, we demonstrate that anterior thalamus in response to different worm stimuli shows the same hierarchy as shown in the behavioral experiment. The successful simulation allows us to provide an explanation of neural mechanisms for visual pattern discrimination. This theory predicts that retinal R 2 cells play a primary role in the discrimination via tectal small pear cells (SP) while R 3 cells refine the feature analysis by inhibition. The simulation also demonstrates that the retinal response to the trailing edge of a stimulus is as crucial for pattern discrimination as to the leading edge. N e w dishabituation hierarchies are predicted by shrinking stimulus size and reversing stimulus-background contrast.

How might a human communication system be bootstrapped in the absence of conventional language? We argue that motivated signs play an important role (i.e., signs that are linked to meaning by structural resemblance or by natural association). An experimental study is then reported in which participants try to communicate a range of pre-specified items to a partner using repeated non-linguistic vocalization, repeated gesture, or repeated non-linguistic vocalization plus gesture (but without using their existing language system). Gesture proved more effective (measured by communication success) and more efficient (measured by the time taken to communicate) than non-linguistic vocalization across a range of item categories (emotion, object, and action). Combining gesture and vocalization did not improve performance beyond gesture alone. We experimentally demonstrate that gesture is a more effective means of bootstrapping a human communication system. We argue that gesture outperforms non-linguistic vocalization because it lends itself more naturally to the production of motivated signs.