I have argued that orthographic processing cannot be understood and modeled without considering the manner in which orthographic structure represents phonological, semantic, and morphological information in a given writing system. A reading theory, therefore, must be a theory of the interaction of the reader with his/her linguistic environment. This outlines a novel approach to studying and modeling visual word recognition, an approach that focuses on the common cognitive principles involved in processing printed words across different writing systems. These claims were (...) challenged by several commentaries that contested the merits of my general theoretical agenda, the relevance of the evolution of writing systems, and the plausibility of finding commonalities in reading across orthographies. Other commentaries extended the scope of the debate by bringing into the discussion additional perspectives. My response addresses all these issues. By considering the constraints of neurobiology on modeling reading, developmental data, and a large scope of cross-linguistic evidence, I argue that front-end implementations of orthographic processing that do not stem from a comprehensive theory of the complex information conveyed by writing systems do not present a viable approach for understanding reading. The common principles by which writing systems have evolved to represent orthographic, phonological, and semantic information in a language reveal the critical distributional characteristics of orthographic structure that govern reading behavior. Models of reading should thus be learning models, primarily constrained by cross-linguistic developmental evidence that describes how the statistical properties of writing systems shape the characteristics of orthographic processing. When this approach is adopted, a universal model of reading is possible. (shrink)

I argue, contra Frost, that when prime lexicality and target density are considered, it is not clear that there are fundamental differences between form priming effects in Semitic and European languages. Furthermore, identifying and naming printed words in these languages raises common theoretical problems. Solving these problems and developing a universal model of reading necessitates the orthographic input code.

In the last decade, reading research has seen a paradigmatic shift. A new wave of computational models of orthographic processing that offer various forms of noisy position or context-sensitive coding have revolutionized the field of visual word recognition. The influx of such models stems mainly from consistent findings, coming mostly from European languages, regarding an apparent insensitivity of skilled readers to letter order. Underlying the current revolution is the theoretical assumption that the insensitivity of readers to letter order reflects the (...) special way in which the human brain encodes the position of letters in printed words. The present article discusses the theoretical shortcomings and misconceptions of this approach to visual word recognition. A systematic review of data obtained from a variety of languages demonstrates that letter-order insensitivity is neither a general property of the cognitive system nor a property of the brain in encoding letters. Rather, it is a variant and idiosyncratic characteristic of some languages, mostly European, reflecting a strategy of optimizing encoding resources, given the specific structure of words. Since the main goal of reading research is to develop theories that describe the fundamental and invariant phenomena of reading across orthographies, an alternative approach to model visual word recognition is offered. The dimensions of a possible universal model of reading, which outlines the common cognitive operations involved in orthographic processing in all writing systems, are discussed. (shrink)

Cognitive Science, Volume 46, Issue 5, May 2022.

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)

It has been recently argued that some machine learning techniques known as Kernel methods could be relevant for capturing cognitive and neural mechanisms (Jäkel, Schölkopf, & Wichmann, 2009). We point out that ‘‘String kernels,’’ initially designed for protein function prediction and spam detection, are virtually identical to one contending proposal for how the brain encodes orthographic information during reading. We suggest some reasons for this connection and we derive new ideas for visual word recognition that are successfully put to the (...) test. We argue that the versatility and performance of String kernels makes a compelling case for their implementation in the brain. (shrink)

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)

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)

Our understanding of the cognitive processes involved in reading has been advanced by computational models that simulate those processes. Unfortunately, most of these models have been developed to explain the reading of English and other alphabetic languages, with relatively fewer efforts to examine whether or not the assumptions of these models also explain what has been learned from other languages and, in particular, non-alphabetic writing systems like Chinese. In this article, we will review those computational models that have been developed (...) to explain the reading of Chinese, with the goal of comparing their theoretical assumptions to those of models that explain the reading of English. Our analysis indicates that there are both points of convergence and divergence between the theoretical assumptions of Chinese versus English models, suggesting that the cognitive systems supporting reading may be differentially influenced by features of the languages and/or writing systems, or that certain theoretical assumptions developed to explain the reading of one language might be adapted to explain the reading of others. (shrink)

Collecting human similarity judgments is instrumental to measuring and modeling neurocognitive representations and has been made more efficient by the multi-arrangement task. While this task has been tested for collecting semantic similarity judgments, it is unclear whether it also lends itself to phonological and orthographic similarity judgments of words. We have extended the task to include these lexical modalities and compared the results between modalities and against computational models. We find that similarity judgments can be collected for all three modalities, (...) although word forms were considered more difficult to sort and resulted in less consistent inter- and intra-rater agreement than semantics. For all three modalities we can construct stable group-level representational similarity matrices. However, these do not capture significant idiosyncratic similarity information unique to each participant. We discuss the potential underlying causes for differences between modalities and their effect on the application of the multi-arrangement task. (shrink)

There is widespread agreement in neuroscience and psychology that the visual system identifies objects and faces based on a pattern of activation over many neurons, each neuron being involved in representing many different categories. The hypothesis that the visual system includes finely tuned neurons for specific objects or faces for the sake of identification, so‐called “grandmother cells”, is widely rejected. Here it is argued that the rejection of grandmother cells is premature. Grandmother cells constitute a hypothesis of how familiar visual (...) categories are identified, but the primary evidence against this hypothesis comes from studies that have failed to observe neurons that selectively respond to unfamiliar stimuli. These findings are reviewed and it is shown that they are irrelevant. Neuroscientists need to better understand existing models of face and object identification that include grandmother cells and then compare the selectivity of these units with single neurons responding to stimuli that can be identified. (shrink)

Manuel Perea, Ana Marcet y Pablo Gomez ERI-Lectura y Departamento de Metodología, Universitat de València, España … Read More →.

Frost proposes a new agenda for reading research, whereby cross-linguistic experiments would uncover linguistic universals to be integrated within a universal theory of reading. We reveal the dangers of following such a call, and demonstrate the superiority of the very approach that Frost condemns.

A universal property of visual word identification is position-invariant letter identification, such that the letter is coded in the same way in CAT and ACT. This should provide a fundamental constraint on theories of word identification, and, indeed, it inspired some of the theories that Frost has criticized. I show how the spatial coding scheme of Colin Davis can, in principle, account for contrasting transposed letter priming effects, and at the same time, position-invariant letter identification.