The authors model the neural mechanisms underlying spatial cognition, integrating neuronal systems and behavioral data, and address the relationships between long-term memory, short-term memory, and imagery, and between egocentric and allocentric and visual and ideothetic representations. Long-term spatial memory is modeled as attractor dynamics within medial–temporal allocentric representations, and short-term memory is modeled as egocentric parietal representations driven by perception, retrieval, and imagery and modulated by directed attention. Both encoding and retrieval/imagery require translation between egocentric and allocentric representations, which are mediated by posterior parietal and retrosplenial areas and the use of head direction representations in Papez’s circuit. Thus, the hippocampus effectively indexes information by real or imagined location, whereas Papez’s circuit translates to imagery or from perception according to the direction of view. Modulation of this translation by motor efference allows spatial updating of representations, whereas prefrontal simulated motor efference allows mental exploration. The alternating temporal–parietal flows of information are organized by the theta rhythm. Simulations demonstrate the retrieval and updating of familiar spatial scenes, hemispatial neglect in memory, and the effects on hippocampal place cell firing of lesioned head direction representations and of conflicting visual and ideothetic inputs.

Associations in episodic memory are formed between items presented close together in time. The temporal context model (TCM) hypothesizes that this contiguity effect is a consequence of shared temporal contexts rather than temporal proximity per se. Using double function lists of paired associates, which include chains of pairs (e.g. A-B, B-C), we examined associations between items that were not presented close together in time but were presented in similar temporal contexts. For instance A and C do not appear together, but both occur in the context of B. Although within-pair associations (e.g. A-B) were asymmetric, across-pair associations (e.g. A-C) showed no evidence for asymmetry. We attempted to describe these transitive associations using two models. One was a heteroassociative model in which the A-C associations resulted from mediated chaining as a result of “stepping through ” the links in the chain. Although this heteroassociative model and TCM make identical predictions regarding simple contiguity effects, the heteroassociative model had great difficulty accounting for the form of transitive associations between items. TCM provided an excellent fit to the data. These data raise the surprising possiblity that episodic contiguity effects do not reflect direct associations between items but rather a process of binding, encoding and retrieval of a gradually-changing

In remembering a list of words, subjects ’ order of recall can reveal the influence of both semantic and temporal associations among items. In this chapter, we examine how well measures of semantic relatedness (e.g., Landauer & Dumais, 1997; Steyvers, Shiffrin, & Nelson, 2004) predict the order of subject’s recalls. Analysis of recall transitions reveal that subtle variations in semantic relatedness strongly influence memory retrieval. Contrary to the view that temporal and semantic similarity strictly compete as retrieval cues, the data reveal that these two factors are separately modifiable, at least under certain conditions. These findings are not easily reconciled within current models of episodic and semantic memory. A central function of episodic memory is to form and utilize associations between items experienced at nearby times. In addition to these newly–formed episodic associations, subjects enter the laboratory with a great deal of knowledge about verbal stimuli. Studying the relation between episodic and pre–existing, or semantic, associations can help shed

A. Redish et al. (2007) proposed a reinforcement learning model of context-dependent learning and extinction in conditioning experiments, using the idea of “state classification ” to categorize new observations into states. In the current article, the authors propose an interpretation of this idea in terms of normative statistical inference. They focus on renewal and latent inhibition, 2 conditioning paradigms in which contextual manipulations have been studied extensively, and show that online Bayesian inference within a model that assumes an unbounded number of latent causes can characterize a diverse set of behavioral results from such manipulations, some of which pose problems for the model of Redish et al. Moreover, in both paradigms, context dependence is absent in younger animals, or if hippocampal lesions are made prior to training. The authors suggest an explanation in terms of a restricted capacity to infer new causes.

of news asymmetries in foreign exchange markets by

The conceptual focus of this dissertation is the ability of humans to target episodic memories, i.e., to re-access past states of the world encoded by the memory system. I describe a framework for understanding this process that relies on the interaction of three cognitive systems in the brain: semantic memory, episodic memory, and a context maintenance system that acts to probe the episodic memory system. I build upon previous studies of these systems, in which each of these cognitive systems is mapped onto a particular anatomical region of the brain. Respectively, these areas are posterior cortex, medial temporal lobe, and prefrontal cortex. This framework is investigated in a series of studies of the free recall paradigm. First, I describe a neuroimaging experiment in which I use pattern classification methods to track the second-by-second fluctuations of patterns of brain activity during free recall. The results of this experiment provide evidence of contextual reinstatement processes during the recall period. These results highlight the idea that context effects on memory organization can be carried out by any brain area that has both a relatively stable pattern of activity during the encoding process, and connections with medial temporal lobe brain regions. Second, a behavioral study manipulates the accessibility of memories by changing encoding

Abstract not found

Both episodic memory and spatial navigation require temporal encoding of the relationships between events or locations. In a linear maze, ordered spatial distances between sequential locations were represented by the temporal relations of hippocampal place cell pairs within cycles of theta oscillation in a compressed manner. Such correlations could arise due to spike ‘‘phase precession’ ’ of independent neurons driven by common theta pacemaker or as a result of temporal coordination among specific hippocampal cell assemblies. We found that temporal correlation between place cell pairs was stronger than predicted by a pacemaker drive of independent neurons, indicating a critical role for synaptic interactions and precise timing within and across cell assemblies in place sequence representation. CA1 and CA3 ensembles, identifying spatial locations, were active preferentially on opposite phases of theta cycles. These observations suggest that interleaving CA3 neuronal sequences bind CA1 assemblies representing overlapping past, present, and future locations into single episodes.

T. Takeyama and Y. Saito at the Olympus Corporation (Tokyo, Japan) for technical assistance with FALI;

The successor representation was introduced into reinforcement learning by Dayan (1993) as a means of facilitating generalization between states with similar successors. Although reinforcement learning in general has been used extensively as a model of psychological and neural processes, the psychological validity of the successor representation has yet to be explored. An interesting possibility is that the successor representation can be used not only for reinforcement learning but for episodic learning as well. Our main contribution is to show that a variant of the temporal context model (TCM; Howard & Kahana, 2002), an influential model of episodic memory, can be understood as directly estimating the successor representation using the temporal difference learning algorithm (Sutton & Barto, 1998). This insight leads to a generalization of TCM and new experimental predictions. In addition to casting a new normative light on TCM, this equivalence suggests a previously unexplored point of contact between different learning systems. 1