Semantic boost on episodic associations: an empirically-based computational model

Words become associated following repeated co-occurrence episodes. This process might be further determined by the semantic characteristics of the words. The present study focused on how semantic and episodic factors interact in incidental formation of word associations. First, we found that human participants associate semantically related words more easily than unrelated words; this advantage increased linearly with repeated co-occurrence. Second, we developed a computational model, SEMANT, suggesting a possible mechanism for this semantic-episodic interaction. In SEMANT, episodic associations are implemented through lateral connections between nodes in a pre-existent self-organized map of word semantics. These connections are strengthened at each instance of concomitant activation, proportionally with the amount of the overlapping activity waves of activated nodes. In computer simulations SEMANT replicated the dynamics of associative learning in humans and led to testable predictions concerning normal associative learning as well as impaired learning in a diffuse semantic system like that characteristic of schizophrenia.     

Learning representations in a gated prefrontal cortex model of dynamic task switching

The prefrontal cortex is widely believed to play an important role in facilitating people's ability to switch performance between different tasks. We present a biologically‐based computational model of prefrontal cortex (PFC) that explains its role in task switching in terms of the greater flexibility conferred by activation‐based working memory representations in PFC, as compared with more slowly adapting weight‐based memory mechanisms. Specifically we show that PFC representations can be rapidly updated when a task switches via a dynamic gating mechanism based on a temporal‐differences reward‐prediction learning mechanism. Unlike prior models of this type, the present model develops all of its internal representations via learning mechanisms as shaped by the demands of continuous periodic task switching. This advance opens up a new domain of research into the interactions between working memory task demands and the representations that develop to meet them. Results on a version of the Wisconsin card sorting task are presented for the full model and a number of comparison networks that test the importance of various model features. Furthermore, we show that a lesioned model produces perseverative errors like those seen in frontal patients.     

Absence of hardly pursued updating in a running memory task

In a running memory span task, the participants are presented with a list of items (e.g. numbers or words) of an unknown length, because this length varies from trial to trial. In one variation of the procedure the participants must report a certain fixed number of items (e.g. four) from the end of the list. According to Morris and Jones (British Journal of Psychology, 81, 111-121, 1990), the recalled items must be updated in memory as the presentation of the list progresses. Ruiz, Elosúa and Lechuga (The Quarterly Journal of Experimental Psychology, 5, 887-905, 2005) noted that an active strategy implies an inhibition in memory of the final discarded items, and did not find results which supported this hypothesis. The aim of this study is to check whether or not participants adopt an active processing strategy in extreme conditions. Experiment 1 uses catch trials, which induce the participants not to discard the first items of the lists, and also short lists (of 4, 7, 8, 9 and 10 items); these could be considered optimal conditions for updating. However, it should also be pointed out that with an upper limit of 10 items per list, participants could try to memorise the whole list in most of the trials. One way to discourage this strategy is including lists well over span (e.g. 14-26 items). The purpose of Experiment 2 was to analyse the 10-item lists in two conditions: within a context of much longer lists (well over span) in most of the trials and within a context of shorter lists (data of Experiment 1). Results in both experiments, from the analysis of location errors, indicate that even in these conditions the participants do not seem to carry out the supposed active updating of the memory set.     

A meta-analysis of the n-back task while driving and its effects on cognitive workload

This study investigates the effect of the n-back task on cognitive workload while driving. Results of 20 studies with over 800 participants in total show a moderate to high mean effect size. That means the n-back task varies cognitive load while driving in a substantial matter. Further analysis reveals several moderator variables: experiments conducted in a driving simulator showed larger effect sizes than on-road studies. This effect decreases with increasing driving simulator fidelity. Furthermore, the specific driving task assignment moderates the effect: lane change task scenarios result in higher effects than other situations. Regarding the different measurement methods of cognitive workload, subjective questionnaires seem to have very high sensitivity. In contrast, n-back performance measures, detection response task measures, and physiological measurements result in moderate effect sizes, and driving performance measures show reduced sensitivity. Regarding different implementations of the n-back task itself, surprisingly, no moderators are found. Overall, the findings highlight the suitability of the n-back task as a method of inducing cognitive load in transportation research. The moderator analysis gives an overview of different methodological designs and how these designs will affect effect sizes.     

The question shapes the answer: the neural correlates of task differences reveal dynamic semantic processing

Task effects in semantic processing were investigated by contrasting the neural activation associated with two semantic categorization tasks (SCT) using event-related fMRI. The two SCTs involved different decision categories: is it an animal? vs. is it a concrete thing? Participants completed both tasks and, across participants, the same core set of items were presented in both tasks. Results showed task differences in the neural activation associated with these items: in the animal SCT there was greater activation in a number of frontal and temporal regions, including left superior and middle temporal gyri, while in the concrete SCT there was greater activation in left medial frontal gyrus and bilaterally in the precentral gyri. These results are interpreted as evidence of top-down modulation of semantic processing; participants make adjustments to optimize performance in a given task and these adjustments have consequences for the activation observed.     

Integrating the Automatic and the Controlled: Strategies in Semantic Priming in an Attractor Network With Latching Dynamics

Semantic priming has long been recognized to reflect, along with automatic semantic mechanisms, the contribution of controlled strategies. However, previous theories of controlled priming were mostly qualitative, lacking common grounds with modern mathematical models of automatic priming based on neural networks. Recently, we introduced a novel attractor network model of automatic semantic priming with latching dynamics. Here, we extend this work to show how the same model can also account for important findings regarding controlled processes. Assuming the rate of semantic transitions in the network can be adapted using simple reinforcement learning, we show how basic findings attributed to controlled processes in priming can be achieved, including their dependency on stimulus onset asynchrony and relatedness proportion and their unique effect on associative, category‐exemplar, mediated and backward prime‐target relations. We discuss how our mechanism relates to the classic expectancy theory and how it can be further extended in future developments of the model.     

Spreading Activation in an Attractor Network With Latching Dynamics: Automatic Semantic Priming Revisited

Localist models of spreading activation (SA) and models assuming distributed representations offer very different takes on semantic priming, a widely investigated paradigm in word recognition and semantic memory research. In this study, we implemented SA in an attractor neural network model with distributed representations and created a unified framework for the two approaches. Our models assume a synaptic depression mechanism leading to autonomous transitions between encoded memory patterns (latching dynamics), which account for the major characteristics of automatic semantic priming in humans. Using computer simulations, we demonstrated how findings that challenged attractor‐based networks in the past, such as mediated and asymmetric priming, are a natural consequence of our present model’s dynamics. Puzzling results regarding backward priming were also given a straightforward explanation. In addition, the current model addresses some of the differences between semantic and associative relatedness and explains how these differences interact with stimulus onset asynchrony in priming experiments.     

The impact of working memory load on task execution and online plan adjustment during multitasking in a virtual environment

Three experiments investigated the impact of working memory load on online plan adjustment during a test of multitasking in young, nonexpert, adult participants. Multitasking was assessed using the Edinburgh Virtual Errands Test (EVET). Participants were asked to memorize either good or poor plans for performing multiple errands and were assessed both on task completion and on the extent to which they modified their plans during EVET performance. EVET was performed twice, with and without a secondary task loading a component of working memory. In Experiment 1, articulatory suppression was used to load the phonological loop. In Experiment 2, oral random generation was used to load executive functions. In Experiment 3, spatial working memory was loaded with an auditory spatial localization task. EVET performance for both good- and poor-planning groups was disrupted by random generation and sound localization, but not by articulatory suppression. Additionally, people given a poor plan were able to overcome this initial disadvantage by modifying their plans online. It was concluded that, in addition to executive functions, multiple errands performance draws heavily on spatial, but not verbal, working memory resources but can be successfully completed on the basis of modifying plans online, despite a secondary task load.     

The role of meaning in contextual cueing: Evidence from chess expertise

In contextual cueing, the position of a search target is learned over repeated exposures to a visual display. The strength of this effect varies across stimulus types. For example, real-world scene contexts give rise to larger search benefits than contexts composed of letters or shapes. We investigated whether such differences in learning can be at least partially explained by the degree of semantic meaning associated with a context independently of the nature of the visual information available (which also varies across stimulus types). Chess boards served as the learning context as their meaningfulness depends on the observer's knowledge of the game. In Experiment 1, boards depicted actual game play, and search benefits for repeated boards were 4 times greater for experts than for novices. In Experiment 2, search benefits among experts were halved when less meaningful randomly generated boards were used. Thus, stimulus meaningfulness independently contributes to learning context–target associations.     

Graph‐Theoretic Properties of Networks Based on Word Association Norms: Implications for Models of Lexical Semantic Memory

We compared the ability of three different contextual models of lexical semantic memory (BEAGLE, Latent Semantic Analysis, and the Topic model) and of a simple associative model (POC) to predict the properties of semantic networks derived from word association norms. None of the semantic models were able to accurately predict all of the network properties. All three contextual models over‐predicted clustering in the norms, whereas the associative model under‐predicted clustering. Only a hybrid model that assumed that some of the responses were based on a contextual model and others on an associative network (POC) successfully predicted all of the network properties and predicted a word's top five associates as well as or better than the better of the two constituent models. The results suggest that participants switch between a contextual representation and an associative network when generating free associations. We discuss the role that each of these representations may play in lexical semantic memory. Concordant with recent multicomponent theories of semantic memory, the associative network may encode coordinate relations between concepts (e.g., the relation between pea and bean, or between sparrow and robin), and contextual representations may be used to process information about more abstract concepts.     

Suppression of irrelevant activation in the horizontal and vertical Simon task differs quantitatively not qualitatively

The Simon effect is usually explained by the assumption that the irrelevant stimulus location automatically activates the corresponding response. In the case of incongruent stimulus–response assignments automatically activated responses therefore have to be suppressed to ensure correct responses. This account, however, has been called into question for other than horizontally arranged visual Simon tasks. We investigated whether there is a qualitative or quantitative difference in suppression of irrelevant activation between horizontally and vertically arranged Simon tasks, using delta-function analyses. Sequential analyses revealed suppression after incongruent trials in both tasks, supporting the idea of a quantitative rather than a qualitative difference between the tasks. We conclude that automatic response activation is weaker in vertical tasks resulting in lower inhibitory demands as compared to horizontal tasks.     

Semantic Memory Search and Retrieval in a Novel Cooperative Word Game: A Comparison of Associative and Distributional Semantic Models

Considerable work during the past two decades has focused on modeling the structure of semantic memory, although the performance of these models in complex and unconstrained semantic tasks remains relatively understudied. We introduce a two-player cooperative word game, Connector (based on the boardgame Codenames), and investigate whether similarity metrics derived from two large databases of human free association norms, the University of South Florida norms and the Small World of Words norms, and two distributional semantic models based on large language corpora (word2vec and GloVe) predict performance in this game. Participant dyads were presented with 20-item word boards with word pairs of varying relatedness. The speaker received a word pair from the board (e.g., exam-algebra) and generated a one-word semantic clue (e.g., math), which was used by the guesser to identify the word pair on the board across three attempts. Response times to generate the clue, as well as accuracy and latencies for the guessed word pair, were strongly predicted by the cosine similarity between word pairs and clues in random walk-based associative models, and to a lesser degree by the distributional models, suggesting that conceptual representations activated during free association were better able to capture search and retrieval processes in the game. Further, the speaker adjusted subsequent clues based on the first attempt by the guesser, who in turn benefited from the adjustment in clues, suggesting a cooperative influence in the game that was effectively captured by both associative and distributional models. These results indicate that both associative and distributional models can capture relatively unconstrained search processes in a cooperative game setting, and Connector is particularly suited to examine communication and semantic search processes.     

The role of context and functionality in the interpretation of quantifiers

The aim of the three experiments that are reported was to investigate the role of context, especially size and functionality, in the interpretation of quantifiers. The studies all used a task in which participants rated the appropriateness of quantifiers describing the number of balls in a bowl. The size of the balls was found to have an effect: Identical numbers of balls were given different ratings depending on ball size. It was also found that quantifiers were rated as more appropriate when the balls were in their natural functional relationship with the bowl (i.e., contained within the bowl), than when the functional relationship was breached (i.e., the balls overflowed the bowl). Tilting the bowl had surprising effects in that it led to some quantifiers being rated as more appropriate. The results are interpreted as indicating that quantifiers carry little specific meaning in themselves but instead derive their meaning from the context in which they occur.     

The effect of working memory load on semantic illusions: What the phonological loop and central executive have to contribute

When asked how many animals of each kind Moses took on the Ark, most people respond with “two” despite the substituted name (Moses for Noah) in the question. Possible explanations for semantic illusions appear to be related to processing limitations such as those of working memory. Indeed, individual working memory capacity has an impact upon how sentences containing substitutions are processed. This experiment examined further the role of working memory in the occurrence of semantic illusions using a dual-task working memory load approach. Participants verified statements while engaging in either articulatory suppression or random number generation. Secondary task type had a significant effect on semantic illusion rate, but only when comparing the control condition to the two dual-task conditions. Furthermore, secondary task performance in the random number generation condition declined, suggesting a tradeoff between tasks. Response time analyses also showed a different pattern of processing across the conditions. The findings suggest that the phonological loop plays a role in representing semantic illusion sentences coherently and in monitoring for details, while the role of the central executive is to assist gist-processing of sentences. This usually efficient strategy leads to error in the case of semantic illusions.     

Selective deficits in episodic feeling of knowing in ageing: A novel use of the general knowledge task

Failure to recall an item from memory can be accompanied by the subjective experience that the item is known but currently unavailable for report. The feeling of knowing (FOK) task allows measurement of the predictive accuracy of this reflective judgement. Young and older adults were asked to provide answers to general knowledge questions both prior to and after learning, thus measuring both semantic and episodic memory for the items. FOK judgements were made at each stage for all unrecalled responses, providing a measure of predictive accuracy for semantic and episodic knowledge. Results demonstrated a selective effect of age on episodic FOK resolution, with older adults found to have impaired episodic FOK accuracy while semantic FOK accuracy remained intact. Although recall and recognition measures of episodic memory are equivalent between the two age groups, older adults may have been unable to access contextual details on which to base their FOK judgements. The results suggest that older adults are not able to accurately predict future recognition of unrecalled episodic information, and consequently may have difficulties in monitoring recently encoded memories.     

Three layers of working memory: Focus-switch costs and retrieval dynamics as revealed by the N-count task

Two experiments explored the process of switching items in and out of the focus of attention using a new paradigm, the N-count task (adapted from Garavan, 1998; N varied from 1 to 4). This task yielded a focus size of one, indicated by a substantial focus-switch cost for 2-count. Additionally, the focus-switch costs in response time increased with working memory load, indicating an effortful search process occurring at a speed of about 240 ms/item. Maintaining and switching to and from a passive load did not increase the focus-switch costs or decrease memory accuracy, indicating that there is no crosstalk between passive and active items. The results support a concentric theory of working memory: a small focus at its core, a surrounding area of (at least) three readily available items referred to as the outer store, and a still wider region of passive storage, possibly more long-term memory than working memory.     

Not only encoding and retrieval: The enactment effect as a function of task preparation

Three experiments examined the implications of adding a fourth preparation stage to the encoding-retention-retrieval stage analysis of memory. Action memory was selected as the research domain. The results demonstrated that systematic variation of the preparation stage yields new insights about enactment effects in memory. Together with effects of enactment in the preparatory stage, enactment was also shown to give differential effects in encoding and retrieval, with interactions between these three factors. The experimental results were discussed in relation to a strategy processing interpretation of action memory.     

The impact of contextual information and a secondary task on anticipation performance: An interpretation using cognitive load theory

When performing under severe time constraints, sports performers use kinematic and contextual information to facilitate anticipation. We examined the relative importance of these two information sources and their impact on cognitive load and anticipation performance. Cognitive load theory predicts that adding more information sources to a task will increase cognitive load in less‐skilled but not skilled performers. Skilled and less‐skilled cricket batters anticipated deliveries from bowlers on a life‐size screen under 4 conditions that manipulated access to contextual information and included a secondary task. The presence of context enhanced anticipation accuracy for both skilled and less‐skilled groups, without affecting cognitive load. Skilled performers used sequencing and game‐related contextual information in addition to kinematic information to facilitate anticipation, whereas both groups reported using information pertaining to opponent positioning. Findings highlight the importance of context in anticipation and suggest that the addition of context may not necessarily negatively impact cognitive load.     

On the uses of language in working and idealized logic

The interpretation of discourse covers a continuum with two extremes: on the one hand, a text considered as an ideal, distant object, and on the other hand, a conversation regarded as a real, present event. On the basis of a distinction between relatively context-invariant propositions and relatively context-dependent statements, it is argued that statements in conversational discourse are easier to interpret than statements in texts, whereas only propositions in symbolic logic can be interpreted with exactitude. In the same way, the interpretation of dialogical arguments proceeds more easily than the interpretation of arguments in texts. While dialogical argumentation requires a dialectical approach, textual argumentation necessitates an imaginative reconstruction of the argument. From this it can be concluded that for different sorts of argumentative discourse diverse sorts of interpretative activities have to be used.