In this article, we apply a special case of holographic representations to letter position coding. We translate different well-known schemes into this format, which uses distributed representations and supports constituent structure. We show that in addition to these brain-like characteristics, performances on a standard benchmark of behavioral effects are improved in the holographic format relative to the standard localist one. This notably occurs because of emerging properties in holographic codes, like transposition and edge effects, for which we give formal demonstrations. (...) Finally, we outline the limits of the approach as well as its possible future extensions. (shrink)

Understanding spoken words involves a rapid mapping from speech to conceptual representations. One distributed feature-based conceptual account assumes that the statistical characteristics of concepts’ features—the number of concepts they occur in and likelihood of co-occurrence —determine conceptual activation. To test these claims, we investigated the role of distinctiveness/sharedness and correlational strength in speech-to-meaning mapping, using a lexical decision task and computational simulations. Responses were faster for concepts with higher sharedness, suggesting that shared features are facilitatory in tasks like lexical decision (...) that require access to them. Correlational strength facilitated responses for slower participants, suggesting a time-sensitive co-occurrence-driven settling mechanism. The computational simulation showed similar effects, with early effects of shared features and later effects of correlational strength. These results support a general-to-specific account of conceptual processing, whereby early activation of shared features is followed by the gradual emergence of a specific target representation. (shrink)

The way of coding letter position has been extensively assessed during the recognition of native words, leading to the development of a new generation of models that assume more flexible letter position coding schemes compared to classical computational models such as the interactive activation model. However, determining whether similar letter position encoding mechanisms occur during the bilingual word recognition has been largely less explored despite its implications for the leading model of bilingual word recognition as it assumes the input-coding scheme (...) of the IA model. In this study, we aimed to examine this issue through the manipulation of the position of the deviant letter of cognate words. Two experiments were conducted with Catalan–Spanish bilinguals and their respective monolingual controls. The results revealed a differential processing for the first letter in comparison to the other letters as well as modulations as a function of language cue, suggesting amendments to the input-coding scheme of the multilink model. (shrink)

Computational modeling and eye-tracking were used to investigate how phonological and semantic information interact to influence the time course of spoken word recognition. We extended our recent models to account for new evidence that competition among phonological neighbors influences activation of semantically related concepts during spoken word recognition . The model made a novel prediction: Semantic input modulates the effect of phonological neighbors on target word processing, producing an approximately inverted-U-shaped pattern with a high phonological density advantage at an intermediate (...) level of semantic input—in contrast to the typical disadvantage for high phonological density words in spoken word recognition. This prediction was confirmed with a new analysis of the Apfelbaum et al. data and in a visual world paradigm experiment with preview duration serving as a manipulation of strength of semantic input. These results are consistent with our previous claim that strongly active neighbors produce net inhibitory effects and weakly active neighbors produce net facilitative effects. (shrink)

Sibley et al. (2008) report a recurrent neural network model designed to learn wordform representations suitable for written and spoken word identification. The authors claim that their sequence encoder network overcomes a key limitation associated with models that code letters by position (e.g., CAT might be coded as C‐in‐position‐1, A‐in‐position‐2, T‐in‐position‐3). The problem with coding letters by position (slot‐coding) is that it is difficult to generalize knowledge across positions; for example, the overlap between CAT and TOMCAT is lost. Although we (...) agree this is a critical problem with many slot‐coding schemes, we question whether the sequence encoder model addresses this limitation, and we highlight another deficiency of the model. We conclude that alternative theories are more promising. (shrink)

Using a cross-modal semantic priming paradigm, both experiments of the present study investigated the link between the mental representations of iconic gestures and words. Two groups of the participants performed a primed lexical decision task where they had to discriminate between visually presented words and nonwords (e.g., flirp). Word targets (e.g., bird) were preceded by video clips depicting either semantically related (e.g., pair of hands flapping) or semantically unrelated (e.g., drawing a square with both hands) gestures. The duration of gestures (...) was on average 3,500 ms in Experiment 1 but only 1,000 ms in Experiment 2. Significant priming effects were observed in both experiments, with faster response latencies for related gesture–word pairs than unrelated pairs. These results are consistent with the idea of interactions between the gestural and lexical representational systems, such that mere exposure to iconic gestures facilitates the recognition of semantically related words. (shrink)

Using a cross‐modal semantic priming paradigm, both experiments of the present study investigated the link between the mental representations of iconic gestures and words. Two groups of the participants performed a primed lexical decision task where they had to discriminate between visually presented words and nonwords (e.g., flirp). Word targets (e.g., bird) were preceded by video clips depicting either semantically related (e.g., pair of hands flapping) or semantically unrelated (e.g., drawing a square with both hands) gestures. The duration of gestures (...) was on average 3,500 ms in Experiment 1 but only 1,000 ms in Experiment 2. Significant priming effects were observed in both experiments, with faster response latencies for related gesture–word pairs than unrelated pairs. These results are consistent with the idea of interactions between the gestural and lexical representational systems, such that mere exposure to iconic gestures facilitates the recognition of semantically related words. (shrink)

Most words in English are ambiguous between different interpretations; words can mean different things in different contexts. We investigate the implications of different types of semantic ambiguity for connectionist models of word recognition. We present a model in which there is competition to activate distributed semantic representations. The model performs well on the task of retrieving the different meanings of ambiguous words, and is able to simulate data reported by Rodd, Gaskell, and Marslen‐Wilson [J. Mem. Lang. 46 (2002) 245] on (...) how semantic ambiguity affects lexical decision performance. In particular, the network shows a disadvantage forwords with multiple unrelated meanings (e.g., bark) that coexists with a benefit for words with multiple related word senses (e.g., twist). The ambiguity disadvantage arises because of interference between the different meanings, while the sense benefit arises because of differences in the structure of the attractor basins formed during learning. Words with few senses develop deep, narrow attractor basins, while words with many senses develop shallow, broad basins. We conclude that the mental representations of word meanings can be modelled as stable states within a high‐dimensional semantic space, and that variations in the meanings of words shape the landscape of this space. (shrink)

As adults age, their performance on many psychometric tests changes systematically, a finding that is widely taken to reveal that cognitive information-processing capacities decline across adulthood. Contrary to this, we suggest that older adults'; changing performance reflects memory search demands, which escalate as experience grows. A series of simulations show how the performance patterns observed across adulthood emerge naturally in learning models as they acquire knowledge. The simulations correctly identify greater variation in the cognitive performance of older adults, and successfully (...) predict that older adults will show greater sensitivity to fine-grained differences in the properties of test stimuli than younger adults. Our results indicate that older adults'; performance on cognitive tests reflects the predictable consequences of learning on information-processing, and not cognitive decline. We consider the implications of this for our scientific and cultural understanding of aging. (shrink)

Spelling errors are ubiquitous in all writing systems. Most studies exploring spelling errors focused on the phonological plausibility of errors. However, unlike typical pseudohomophones, spelling errors occur in naturally produced written language. We investigated the time course of recognition of the most frequent orthographic errors in Russian and the effect of word frequency on this process. During event-related potentials recording, 26 native Russian speakers silently read high-frequency correctly spelled words, low-frequency correctly spelled words, high-frequency words with errors, and low-frequency words (...) with errors. The amplitude of P200 was more positive for correctly spelled words than for misspelled words and did not depend on the frequency of the words. In addition, in the 350–500-ms time window, we found a more negative response for misspelled words than for correctly spelled words in parietal–temporal-occipital regions regardless of word frequency. Considering our results in the context of a dual-route model, we concluded that recognizing misspelled high-frequency and low-frequency words involves common orthographic and phonological processes associated with P200 and N400 components such as whole word orthography processing and activation of phonological representations correspondingly. However, at the 500–700 ms stage, error recognition depends on the word frequency. One possible explanation for these differences could be that at the 500–700 ms stage recognition of high-frequency misspelled and correctly spelled words shifts from phonological to orthographic processes, while low-frequency misspelled words are accompanied by more prolonged phonological activation. We believe these processes may be associated with different ERP components P300 and N400, reflecting a temporal overlap between categorization processes based on orthographic properties for high-frequency words and phonological processes for low-frequency words. Therefore, our results complement existing reading models and demonstrate that the neuronal underpinnings of spelling error recognition during reading may depend on word frequency. (shrink)

Recent research has found that the omission of accent marks in Spanish does not produce slower word identification times in go/no-go lexical decision and semantic categorization tasks [e.g., cárcel = carcel], thus suggesting that vowels like á and a are represented by the same orthographic units during word recognition and reading. However, there is a discrepant finding with the yes/no lexical decision task, where the words with the omitted accent mark produced longer response times than the words with the accent (...) mark. In Experiment 1, we examined this discrepant finding by running a yes/no lexical decision experiment comparing the effects for words and non-words. Results showed slower response times for the words with omitted accent mark than for those with the accent mark present, thus suggesting a bias toward a “word” response for accented items in the yes/no lexical decision task. To test this interpretation, Experiment 2 used the same stimuli with a blocked design and a go/no-go lexical decision task. Results showed similar response times to words regardless of whether the accent mark was omitted. This pattern strongly suggests that the longer response times to words with an omitted accent mark in yes/no lexical decision experiments are a task-dependent effect rather than a genuine reading cost. (shrink)

Visual word recognition is facilitated by the presence of orthographic neighbors that mismatch the target word by a single letter substitution. However, researchers typically do not consider where neighbors mismatch the target. In light of evidence that some letter positions are more informative than others, we investigate whether the influence of orthographic neighbors differs across letter positions. To do so, we quantify the number of enemies at each letter position (how many neighbors mismatch the target word at that position). Analyses (...) of reaction time data from a visual word naming task indicate that the influence of enemies differs across letter positions, with the negative impacts of enemies being most pronounced at letter positions where readers have low prior uncertainty about which letters they will encounter (i.e., positions with low entropy). To understand the computational mechanisms that give rise to such positional entropy effects, we introduce a new computational model, VOISeR (Visual Orthographic Input Serial Reader), which receives orthographic inputs in parallel and produces an over‐time sequence of phonemes as output. VOISeR produces a similar pattern of results as in the human data, suggesting that positional entropy effects may emerge even when letters are not sampled serially. Finally, we demonstrate that these effects also emerge in human subjects' data from a lexical decision task, illustrating the generalizability of positional entropy effects across visual word recognition paradigms. Taken together, such work suggests that research into orthographic neighbor effects in visual word recognition should also consider differences between letter positions. (shrink)