We present a neural network model that shows how the prefrontal cortex, interacting with the basal ganglia, can maintain a sequence of phonological information in activation-based working memory (i.e., the phonological loop). The primary function of this phonological loop may be to transiently encode arbitrary bindings of information necessary for tasks | the combinatorial expressive power of language enables very exible binding of essentially arbitrary pieces of information. Our model takes advantage of the closed-class nature of phonemes, which allows dierent neural representations of all possible phonemes at each sequential position to be encoded. To make this work, we suggest that the basal ganglia provide a region-speci c update signal that allocates phonemes to the appropriate sequential coding slot. To demonstrate that exible, arbitrary binding of novel sequences can be supported by this mechanism, we show that the model can generalize to novel sequences after moderate amounts of training.

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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

This book is about the interface between natural language and the sensorimotor system. It is obvious that there is an interface between language and sensorimotor cognition, because we can talk about what we see and do. The main proposal in the book is that the interface is more direct than is commonly assumed. To argue for this proposal I focus on a simple concrete episode—a man grabbing a cup—which can be reported in a simple transitive sentence (e.g. the English sentence The man grabbed a cup). In the first part of the book I present a detailed model of the sensorimotor processes involved in experiencing this episode, both as the agent bringing it about and as an observer watching it happen. The model draws on a large body of research in neuroscience and psychology. I also present a model of the syntactic structure of the associated transitive sentence, developed within the entirely separate discipline of theoretical linguistics. This latter model is a version of Chomsky’s ‘Minimalist ’ syntactic theory, which assumes that a sentence reporting the episode has the same underlying syntactic structure (called ‘logical form’) regardless of which language it is in. My main proposal is that these two independently motivated models are in fact closely

Abstract. Three experiments with an arithmetic working memory task examine the object switch effect first reported by Garavan (1998), which was interpreted as evidence for a focus of attention within working memory. Experiments 1a and 1b showed object switch costs with a task that requires selective access to items in working memory, but did not involve counting, and did not require updating of working memory contents, thus ruling out two alternative explanations of Garavan’s results. Experiment 2 showed object switch costs with a task that required no selective access to working memory contents, but involved updating, thus providing evidence for a second component to the overall object switch costs. Further analyses revealed that the object switch cost increased with memory set size; that there were (smaller) switch costs when the switch was to an item of the same type; that repeating an arithmetic operation does not have the same effect as repeating the object it is applied to; and that object switching is not mediated by backward inhibition of the previously focused object. Key words: working memory, attention, switching, mental model, anaphor resolution, spatial distance effect One function of working memory is to hold a number of units of information available for processing. Processing often requires selection of a subset of the working memory contents as the object of a manipulation. For example, mental addition of two

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Memory for order is fundamental in everyday cognition, supporting basic processes like causal inference. However, theories of order memory are narrower, if anything, than theories of memory generally. The memory-in-chains (MIC) model improves on existing theories by explaining a family of order memory effects, by explaining more processes, and by making strong predictions. This paper examines the MIC model's explanation of primacy and recency effects, and the prediction that primacy should dominate recency. This prediction is supported by existing data sets, suggesting that Estes's (1997) perturbation model, dominant among theories of order memory, is incorrect. Fits to data are presented and compared with fits of other models.

The authors argue that human sequential learning is often but not always characterized by a shift from stimulus- to plan-based action control. To diagnose this shift, they manipulated the frequency of 1st-order transitions in a repeated manual left–right sequence, assuming that performance is sensitive to frequencyinduced biases under stimulus- but not plan-based control. Indeed, frequency biases tended to disappear with practice, but only for explicit learners. This tendency was facilitated by visual–verbal target stimuli, response-contingent sounds, and intentional instructions and hampered by auditory (but not visual) noise. Findings are interpreted within an event-coding model of action control, which holds that plans for sequences of discrete actions are coded phonetically, integrating order and relative timing. The model distinguishes between plan acquisition, linked to explicit knowledge, and plan execution, linked to the action control mode.

We tested two explanations of the phonological similarity effect in verbal short-term memory: The confusion hypothesis assumes that serial positions of similar items are confused. The overwriting hypothesis states that similar items share feature representations, which are overwritten. Participants memorised a phonologically dissimilar list of CVC-trigrams �Experiment 1) or words �Experiment 2 and 3) for serial recall. In the retention interval they read aloud other items. The material of the distractor task jointly overlapped one item of the memory list. The recall of this item was impaired, and the effect was not based on intrusions from the distractor task alone. The results provide evidence for feature overwriting as one potential mechanism contributing to the phonological similarity effect. One of the most robust findings in immediate verbal recall tasks is the phonological similarity effect: Increasing the similarity of to-be-remembered verbal material decreases memory performance in serial recall �Conrad, 1964) This effect was mainly attributed to confusion of similar items �Wickelgren, 1965), but destruction of the memory

We present a neural network model of verbal working memory which attempts to illustrate how a few simple assumptions about neural computation can shed light on cognitive phenomena associated with the serial recall of verbal material. We assume that neural representations are distributed, that neural connectivity is massively recurrent, and that synaptic efficiency is modified based on the correlation between pre- and post-synaptic activity (Hebbian learning). Together these assumptions give rise to emergent computational properties that are relevant to working memory, including short-term maintenance of information, time-based decay, and similarity-based interference. We instantiate these principles in a specific model of serial recall and show how it can both simulate and explain a number of standard cognitive phenomena associated with the task, including the effects of serial position, word length, articulatory suppression (and its interaction with word length), and phonological similarity.