Visual Salience and Orthographic Word Processing in Reading and Recognition: A Signal Detection Approach

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In the study we investigate how holistic visual signals, such as overall word form and initial-letter prominence, impact reading accuracy. A sample of 33 postgraduate students took part in a signal detection task with four word-pair conditions: uncoloured transposed, coloured transposed, altered starting, and altered ending. Signal Detection Theory was used to quantify perceptual discrimination by measuring sensitivity (d′) and response bias (c). Results revealed enhanced sensitivity for words with initial-letter changes and a liberal response bias when colour was introduced, whereas end-letter modifications had minimal impact. These results emphasize the importance of word-initial letters and the modulatory impact of visual salience in reading processes. Flexible orthographic coding, visual attention and structural elements are crucial to word recognition. Implications include education, technology, psychology, and therapeutic applications, emphasising the difficulties of reading comprehension as well as the need of sequential and holistic perception theories. Future research could explore combined stimuli impacts and cross-language processes for enhanced understanding with the simultaneous use of neuroimaging techniques. Word Recognition Language Processing Psycholinguistics Signal Detection Transposition Introduction In psycholinguistics, the "Cambridge effect" refers to readers' ability to accurately recognize English words even when the beginning and the final letters are internally rearranged. Although this phenomenon was not created at Cambridge University, as suggested by its misleading name (Velan & Frost, 2007 ), its empirical reality differs greatly from sequential models of word perception that prioritize letter-by-letter processing. This implies that word recognition may rely on both accurate feature analysis and holistic processing. Transposition is the rearrangement of linguistic parts like letters within words or words within phrases, while priming is the way that earlier exposure to a stimulus affects the processing of a subsequent stimulus. These processes explain how the brain organizes and interprets linguistic information (Branigan et al., 1995 ; Pickering & Branigan, 1999 ). The ability to perceive words visually depends on processing certain language properties, such as morphology, which includes a word's formation and structural elements. Variations in morphology can affect reading, especially when they change a word's well-known structure. However, the ability to read English words with transposed letters supports a Gestalt-like model of visual word recognition in which the word's overall shape is viewed as a single coherent unit rather than a sequence of letters. The transposed-letter resemblance effect demonstrates this, as non-words created by transposing two letters nevertheless activate the intended word's lexical representation. (Perea et al., 2023 ). Furthermore, distortions in a word's overall structure do not significantly impair reading until important visual cues, such as the relative size of lowercase letters, are altered (Smith et al., 1969 ). These findings corroborate the "whole word" recognition method, which prioritizes the perception of distinct visual configurations above individual letter-by-letter analysis (Smith, 1969 ). The visual span, or the spatial area where letters can be recognised without eye movements, affects how well visual word recognition works. This perceptual window is expanded by lexical and supra-lexical information improving improves reading efficiency (Veldre et al., 2023 ). There are two main ways in which this expansion takes place. First, as readers depend on positional regularities to support early stages of word recognition, being familiar with word-initial letter sequences promotes quick lexical access and enhances foveal processing (Lima & Inhoff, 1985 ). These lexical representations not only help readers recognize the currently fixated word, but they also facilitate the extraction of parafoveal information, which allows them to start processing incoming words prior to direct fixation (Veldre & Andrews, 2015 ). Second, compared to single vowels or clusters of consonants, orthographic rimes function as more dependable perceptual units with faster reading rates and increased identification accuracy are facilitated by their consistency (Treiman et al., 1995 ). Word recognition is significantly impacted by the location of letter transpositions as the differences are most noticeable when transpositions take place close to the start of a word. This illustrates how a word's beginning letters have a greater impact on lexical access even when there is no parafoveal preview (White et al., 2008 ). Transposed letter non-words often exhibit measurable behavioural impacts because of their remarkable perceptual similarity to actual words. In lexical judgment tests, such non-words are far more challenging to reject than substitution non-words. The findings are similar across phrase contexts, with a transposed letter word generating more lexical activation than a substitute word (Mirault & Grainger, 2021 ). Orthographic coding involves several paths for processing letter identity and location. While letter identity recognition is quite rigid, letter position coding is rather flexible (Hasenäcker & Schroeder, 2022 ). This adaptability is obvious in transposed-letter effects, where non-words produced by transposing internal letters can activate the semantic representation of their base words nearly as efficiently as accurately written primes. In contrast, substitution non-words lack comparable priming effects (Perea & Lupker, 2003 ). Linguistic context controls the strength of transposed letter priming as high semantic predictability during sentence processing pre-activates certain letter identities and their positions, removing transposition effects in constraining contexts while maintaining them in neutral or non-constraining ones (Luke & Christianson, 2012 ). Furthermore, morphological limitations limit the flexibility of transposition. Word recognition is equally disrupted by letter transpositions across morpheme divisions in inflected words as it is by whole letter substitutions (Luke & Christianson, 2013 ). Lexical and orthographic processing are significantly impacted by changes in visual formatting. For example, differences in letter case between upper and lower case have a greater impact on word recognition within a word, than between words since case variations within words decrease reading effectiveness (Bowey, 1996 ; Fournet et al., 2023 ). Colour also has varied impacts: while it helps with visual grouping and segmentation (Pinna & Deiana, 2014 ), adjustments like syllable-specific colouring or contrast shifts diminish, but not eliminate, transposed-letter effects. This shows that, even in the presence of visual noise, abstract orthographic representations continue to impact position coding (Marcet et al., 2019 ). Furthermore, colour preferences introduce processing asymmetries: pseudowords are recognized faster when presented in evolutionarily salient colours such as blue or red, whereas real words demonstrated processing advantages in green independent of valence, demonstrating an association between automatic colour processing and higher-order lexical access (Bortolotti et al., 2024 ). developed Signal Detection Theory (SDT), a mathematical framework particularly beneficial for the evaluation of perceptual thresholds in word recognition because it provides a reliable approach for evaluating an individual's sensitivity to detecting signals, such as words, in the presence of background noise. The assumption is based on an analysis of decision-making under uncertainty, specifically yes/no tasks with a mix of signal and noise trials. In these tasks, responses are dictated by a decision variable, and the outcome, whether a participant detects the presence or absence of a signal, depends on whether this variable exceeds a predetermined criterion. While the findings of research into transposition, priming, and orthography have been consistent, significant methodological constraints remain. A research gap exists as most studies have focused on isolated factors such as priming, transposition, or signal-based cues like colour or letter case. To address this gap, the present study employs an innovative multi-series approach that investigates how Gestalt-based holistic processing and semantic mechanisms jointly influence visual word perception. We test whether words can be distinguished from signal-based noise such as transposed, altered, or coloured variant, using Signal Detection Theory. We hypothesize that whole-word perception would be resilient to positional changes if there were minimal variation in detection rates or reading times between conditions. Therefore, as proposed by the Cambridge effect, we directly evaluate whether English word recognition functions holistically, irrespective of internal letter order or remains significantly affected by font colour and letter position. Method Research Design: The present study undertook a quantitative experimental design with a within sample approach to assess repeated measures. The study seeks to identify how the participants are able to respond to various stimuli and are they able to distinguish it within themselves. Research Question: To what extent does the visual recognition and discrimination capability in English-speaking individuals influence their overall experience in terms of reading comprehension, ease differentiating textual features, and their ability to detect signals within written materials? Objectives: To assess the presence of difference in detection and bias between uncoloured words and coloured words. To assess the presence of difference in detection and bias between uncoloured words and words whose first letters are interchanged. To assess the presence of difference in detection and bias between uncoloured words and words whose last letters are interchanged. Sample: Following G*Power analysis, a sample size of 33 participants residing in Bangalore city was determined (α = 0.05, expected effect size = 0.5, Power = 0.75, n = 32). The participants were postgraduate students enrolled full-time in English-medium courses to assure proficiency in both written and verbal comprehension of the English language, so reducing any confounding factors. Purposive sampling was used to identify participants, owing to its ease and efficiency in recruiting people from a specified demographic. Inclusion Criteria: Participants must to be enrolled full-time in an educational program at the point of time. Participants should possess education from an English-medium school. Participants had to have studied English as their first language since the first grade. Participation is contingent upon having normal or corrected-to-normal eyesight. Exclusion Criteria: Participants diagnosed with language-related difficulties or disorders as reading challenges may affect test results Participants with any diagnosed learning disorders. Participants diagnosed with neurological or neurodevelopmental disorders, including a history of childhood seizures. Participants with colour blindness. Statistical Techniques: The signal detection theory was used to score the responses. The sensitivity index d' was measured using the formula: d'=Z (Hit Rate)- Z (False Alarm Rate) adjusting for extreme values as per corrections recommended by (Hautus, 1995 ). Group differences were assessed using Friedman's test, and pairwise differences were evaluated post-hoc using the Wilcoxon signed rank test. The analysis was conducted using R Studio and SPSS. Procedure: The participants were instructed to identify words presented on a screen, some of which were correctly spelled while others had jumbled letters. Participants were asked to press "A" if they perceived the word as correctly spelled and "L" if they thought otherwise. After confirming understanding, the task began. Words were presented on a separate screen measuring 20 cm x 32 cm, using Arial font size 32. Participants sat approximately 2.5 feet from the screen. Their responses were recorded and exported into a CSV file. Stimuli: The stimulus set comprised 126 words, carefully chosen to reflect common language usage in India. Each category included 22 words, distributed across word lengths from three to eight letters. Categories varied based on word appearance: Category 1 contained uncoloured normal words, Category 2 had uncoloured words with transposed letters, Category 3 presented normal words in colour, and Category 4 featured coloured words with transposed letters. Categories 5 and 6 included words with initial and final letters jumbled, respectively. This systematic approach allowed for a thorough investigation into word processing under different conditions targeting cognitive processes involved in word recognition. Results Table 1 Probabilities of hits and false alarm rates in detection and bias Pairs Condition Probabilities Signal Noise N Hits False Alarm d' c Pair 1 Uncoloured Transposed Uncoloured Untransposed 33 0.78 0.21 1.72 0.05 Pair 2 Coloured Transposed Coloured Untransposed 33 0.83 0.25 1.84 -0.12 Pair 3 Altered Beginning Uncoloured Untransposed 33 0.86 0.21 2.13 -0.15 Pair 4 Altered Ending Uncoloured Untransposed 33 0.76 0.21 1.64 0.08 The study was conducted on a sample on 33 postgraduate students (5 males and 28 females) with a mean age of 21.5 years. The data from each stimulus category was grouped in pairs in order to collect the sensitivity index and response bias. In Pair 1, the participants consistently displayed the capacity to distinguish signal from noise with low response bias, creating a baseline for comparison. Pair 2 showed a slight increase in sensitivity; however, this was accompanied by a shift toward a more liberal decision threshold, implying that the inclusion of colour may have influenced participants to adopt a more affirmative response tendency. Pair 3 generated the highest level of sensitivity, demonstrating that transpositions affecting the first letters of words were most noticeable and easy to identify. In contrast, Pair 4 had lower sensitivity and a more moderate response bias, indicating that end-letter modifications were less perceptually disruptive. These data indicate that both visual prominence e.g., colour and structural position of modifications at the beginning or ending influence detection accuracy and reaction tendencies in visual word recognition tasks. Table 2 Friedman test for group differences between pairs in d' and c Measure n Chi-Square Assymp. Sig. Kendall’s W d' 33 22.938 0.000 0.232 c 33 22.577 0.000 0.228 A Friedman test was used to determine if sensitivity index d′ and response bias c differed substantially across the four experimental conditions. The pairs in the measure of sensitivity index yielded a weak effect size indicating an approximate 23% of variance (χ²=22.938, p < 0.001). Similarly, the response bias showed a significant but weak effect size indicating an approximate 22% of variance between the pairs (χ²=22.577, p < 0.001). Table 3 Post-hoc Wilcoxon signed rank test for pair wise differences Measure Comparison Z Asymp. Sig. r d' Pair 2 X Pair 1 -1.019 0.308 -0.177 Pair 3 X Pair 1 -3.755 0.000 -0.653 Pair 4 X Pair 1 -1.230 0.219 -0.214 c Pair 2 X Pair 1 -2.70 0.006 -0.470 Pair 3 X Pair 1 -3.756 0.000 -0.653 Pair 4 X Pair 1 -1.253 0.210 -0.218 To determine the specific condition differences that contributed to the significant Friedman test results, post hoc pairwise comparisons using the Wilcoxon Signed-Rank test were carried out. A statistically significant difference was identified between Pair 3 altered beginning and Pair 1 uncoloured transposed (Z=-3.755, p < 0.001, r= -0.653) indicating a substantially higher level of sensitivity when alterations occurred at the beginning of words. Comparisons between Pair 2 coloured transposed and Pair 1 uncoloured transposed (Z = − 1.02, p = .308), and between Pair 4 altered ending and Pair 1 uncoloured transposed (Z = − 1.23, p = .219), did not reach statistical significance, suggesting that these conditions did not have differences in detection performance compared to the baseline. Significant differences in response bias were observed between Pair 2 coloured transposed and Pair 1 (Z = -2.70, p = .006, r = -0.470) and between Pair 3 altered beginning and Pair 1 (Z = -3.76, p < .001, r = -0.653), indicating a shift towards a more liberal response criterion when color transpositions or initial letter alterations were introduced. The comparison of Pair 4 and Pair 1 (Z = -1.25, p = .210, r = -0.218) yielded no statistically significant difference, suggesting that changes in endings had little effect on response thresholds. The findings demonstrated structural and visual modifications have varied effects on perceptual sensitivity and detection processes, with initial letter adjustments and coloured transpositions having the greatest influence across both measures. Discussion The study used signal detection theory (SDT) to investigate how orthographic and perceptual changes, especially color, initial-letter transposition, and terminal-letter transposition, affect visual word identification. Thirty-three postgraduate students completed detection tasks in four different within-subject conditions ie baseline transposed letters without color, color-enhanced transpositions, initial-letter changes, and final-letter alterations. The results indicated a statistically significant impacts in sensitivity and response bias best explain how visual salience and structural disruption influence reading processes. The predominance of first letters in visual word identification relates to the well-known fact that the primary letters of a word is processed more effectively and plays an important part in recognizing the word. Research repeatedly demonstrates a significant advantage for the first letter position, most likely due to quick spatial attention deployment to the start of the word. Multiple trials indicate that the beginning letter of a word is identified more precisely and rapidly than other locations, even after accounting for visual matching and decision processes. This impact is consistent across word orientations ie horizontal and vertical and is not explained by simple perceptual matching or post-perceptual choice techniques. Instead of serial processing or decision biases, the beneficial effect is associated with a rapid, automatic allocation of spatial attention to the word's beginning once it occurs (Aschenbrenner et al., 2017 ). Advanced temporal sampling investigations reveal that, while all letter positions are processed concurrently, each position, including the first, has different temporal processing characteristics. This indicates that the first letter isn't processed in strict serial sequence, but it nonetheless sticks out owing to distinct attentional or perception mechanisms (Arguin & Fortier St-Pierre, 2023). The unique processing of each letter location lends credence to the notion that the beginning letter's dominance stems from both parallel processing and position-specific attentional effects (Arguin & Fortier-St-Pierre, 2023 ; Aschenbrenner et al., 2017 ). The influence of orthographic neighbors - words that vary by one letter, varies by letter position, with the initial letter frequently being more informative and influential in word identification tests (Luthra et al., 2020 ). Flexible orthographic coding is the brain's capacity to recognize words even when the order of letters or syllables is changed, a feature that is frequently researched using transposition effects. This flexibility is essential for efficient reading and is influenced by both the features of writing systems and reading experiences. Readers frequently misinterpret words with transposed internal letters e.g., "jugde" for "judge", implying that letter position is conveyed flexibly rather than rigorously. This effect is evident early in reading development and extends throughout adulthood, notably for letter strings compared to non-letter strings, indicating that a specific mechanism for letter position coding develops with reading experience (Hasenäcker & Schroeder, 2022 ; Massol et al., 2025 ). The extent of flexibility in letter position encoding varies by language and script. Korean Hangul and Chinese exhibit both similarities and variations in transposition effects, which are impacted by script construction and word proximity (Z. Liu et al., 2025 ). People with great orthographic competence, such as Scrabble players, had less transposed-letter effects, showing that experience can influence letter position coding (Perea et al., 2016 ). Models such as open-bigram representations and neurological evidence support the notion that letter position coding is both adaptable and specialised. Recognition memory and reading experiments support the open-bigram hypothesis, which proposes that the brain encodes not just individual letters but also pairs of letters in any sequence, hence explaining the observed flexibility (Zhang & Osth, 2024 ). Visual perception features e.g., color and contrast can alter but not remove transposition effects, emphasizing both perceptual and abstract orthographic components (Marcet et al., 2019 ). Spatial attention has a substantial impact on how terminal letters are processed in word recognition. Directing spatial attention to certain letter locations, particularly at the beginning of a word, improves identification accuracy and lowers mistakes, with the first letter benefiting the most from attentional concentration. Terminal-letter positions have a distinct function in visual word recognition, although their influence is not necessarily dominating, restricted, or context-dependent. Endogenous attention, when focused on a specific letter position, is more beneficial than reflexive or exogenous. Endogenous signals are highly effective in reducing mistakes caused by letters being confused for one another, particularly in packed or complicated letter strings. Valid spatial cues particularly endogenous ones minimize position swap mistakes, which occur when a letter is reported from the incorrect place, more efficiently than misidentification errors. This shows that spatial attention aids in the maintenance of precise letter order, which is required for accurate word recognition (Ramamurthy et al., 2021a , b ). Predictive coding models suggest that the brain pre-activates orthographic and lexical-semantic representations before a word appears, especially in predictable contexts. This pre-activation sharpens neural responses, making word recognition more efficient. Neuroimaging and electrophysiological research have shown context-based facilitation occurs in many stages. Early impacts appear in visual and orthographic processing regions, whereas later effects are associated with lexical-semantic processing. Top-down feedback from higher-level lexical regions can influence early word form processing, enabling interactive rather than simply feedforward models (Kim & Lai, 2012 ; Y. Liu et al., 2021 ). Lexical expectations, influenced by context, improve identification of common words and those with strong semantic connotations (Eisenhauer et al., 2019 ). However, complete prediction of precise word forms is uncommon, with the brain frequently anticipating semantic or morpho-syntactic elements, which aids reading (Luke & Christianson, 2016 ). Lexical expectations can impair identification of non-words, highlighting the distinctiveness of predictive facilitation for real words (Hendrix & Sun, 2021 ). The ramifications of initial-letter primacy and colour effects are significant in education, design, and assistive technology. Enhancing starting letters with typographic emphasis or color may improve reading accuracy and fluency, as observed in therapies for dyslexia and early readers. For user-interface designers, increasing visual salience in textual displays can boost user confidence without affecting interpretability. These findings show how cognitive research may directly influence real-world practice. The limited, homogeneous sample of just postgraduate students is one of the study's drawbacks. Future study should include more diverse populations, such as children and those with reading difficulties. Integrating reaction-time measurements or neurophysiological recordings such as EEG/ERP and eye-tracking might reveal the temporal dynamics of letter-position effects. Manipulating color signals more systematically, varying hue intensity, background contrast, or spatial placement could reveal their impact on response bias. Finally, cross-linguistic replication is required, particularly in scripts with non-left-to-right orientation, to evaluate whether the initial-letter advantage is consistent across orthographies. Conclusion We used signal detection theory to investigate how structural and perceptual modifications, especially color, initial-letter, and end-letter adjustments, affect visual word identification. The findings showed that initial-letter transpositions significantly raised sensitivity and altered response bias, emphasizing the importance of word-onset in lexical access. Colour impacted decisional criteria without improving detection, but end-letter alterations had no effect. The findings provide evidence for variable orthographic coding as well as the impact of visual salience on recognition processes, helping to understand how attentional and structural elements influence reading. Declarations Competing Interests: The authors have no competing or conflict of interests to declare. Consent All ethical guidelines were adhered to during the conduction of the study. Informed consent was obtained from all the participants prior to the conduction of the experiment. Data and Materials availability The data may be availed based on reasonable request from the Corresponding Author Funding: No funds, grants, or other support was received for the present study. Author Contribution HCR: Conceptualization, conducting experiment, writing manuscript first draft, reviewing manuscript; FF: Conceptualization, conducting experiment, reviewing manuscript; LL: Supervision, Conceptualization, reviewing manuscript. Acknowledgement The authors acknowledge the assistance of Mr Shreyas Mallya. References Arguin, M., & Fortier-St-Pierre, S. (2023). The spatiotemporal dynamics of letter processing in visual word recognition elucidated by random temporal sampling. Journal of Vision , 23 (9), 4703–4703. https://doi.org/10.1167/JOV.23.9.4703 Aschenbrenner, A. J., Balota, D. A., Weigand, A. J., Scaltritti, M., & Besner, D. (2017). The first letter position effect in visual word recognition: The role of spatial attention. 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Journal of Experimental Psychology Human Perception and Performance , 34 (5), 1261. https://doi.org/10.1037/0096-1523.34.5.1261 Zhang, L., & Osth, A. F. (2024). Modelling orthographic similarity effects in recognition memory reveals support for open bigram representations of letter coding. Cognitive Psychology , 148 , 101619. https://doi.org/10.1016/J.COGPSYCH.2023.101619 Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterials.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7292889","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":499098533,"identity":"2746b5a8-83f7-4183-8e68-82ee4ffa56a6","order_by":0,"name":"Hansel Chris Rodrigues","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIiWNgGAWjYBACAzB5AIjZmw8+AFI8fMRqkWDgOZYM4vCwEa9FIsdMAsQmqMWc/ezhzzxnbOr4G3LMKr/m2MmwMTA/fHQDjxbLnrw0aZ4baRISB46V3Zbdlgx0GJuxcQ4+hx3IMWPm+XBYguFg87bbktuYgVp42KTxajn/xvgzSIv8YQazYslt9URouZFjAHTYYQmDYyxmjB+3HSZGyxszyTln0iQ3nmFLlmbcdpyHjZmQX87nGH94c8yGX+7+44Mff26rtudnb374GJ8WFMDMAyaJVQ4CjD9IUT0KRsEoGAUjBgAACHRI9MB9gf8AAAAASUVORK5CYII=","orcid":"","institution":"Kristu Jayanti College","correspondingAuthor":true,"prefix":"","firstName":"Hansel","middleName":"Chris","lastName":"Rodrigues","suffix":""},{"id":499098535,"identity":"10f90768-8664-48d5-9a5f-f2cb9fa9285e","order_by":1,"name":"Flavia Furtado","email":"","orcid":"","institution":"Kristu Jayanti College","correspondingAuthor":false,"prefix":"","firstName":"Flavia","middleName":"","lastName":"Furtado","suffix":""},{"id":499098536,"identity":"e1ed9b89-b8c2-434f-849a-7d7859a37619","order_by":2,"name":"Lokesh L","email":"","orcid":"","institution":"Kristu Jayanti College","correspondingAuthor":false,"prefix":"","firstName":"Lokesh","middleName":"","lastName":"L","suffix":""}],"badges":[],"createdAt":"2025-08-04 15:53:15","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7292889/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7292889/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90608497,"identity":"595052c1-a064-4b68-862e-41495b05af26","added_by":"auto","created_at":"2025-09-04 16:16:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":588540,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7292889/v1/ae5c70b2-b3a5-4678-8ed2-40158b0d9d32.pdf"},{"id":89548026,"identity":"d30c8154-551d-48d7-afff-a8e7af0f9879","added_by":"auto","created_at":"2025-08-21 07:39:46","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":15284,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-7292889/v1/9ffe9824a2ff12a94f19aa52.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Visual Salience and Orthographic Word Processing in Reading and Recognition: A Signal Detection Approach","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn psycholinguistics, the \"Cambridge effect\" refers to readers' ability to accurately recognize English words even when the beginning and the final letters are internally rearranged. Although this phenomenon was not created at Cambridge University, as suggested by its misleading name (Velan \u0026amp; Frost, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), its empirical reality differs greatly from sequential models of word perception that prioritize letter-by-letter processing. This implies that word recognition may rely on both accurate feature analysis and holistic processing. Transposition is the rearrangement of linguistic parts like letters within words or words within phrases, while priming is the way that earlier exposure to a stimulus affects the processing of a subsequent stimulus. These processes explain how the brain organizes and interprets linguistic information (Branigan et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Pickering \u0026amp; Branigan, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1999\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe ability to perceive words visually depends on processing certain language properties, such as morphology, which includes a word's formation and structural elements. Variations in morphology can affect reading, especially when they change a word's well-known structure. However, the ability to read English words with transposed letters supports a Gestalt-like model of visual word recognition in which the word's overall shape is viewed as a single coherent unit rather than a sequence of letters. The transposed-letter resemblance effect demonstrates this, as non-words created by transposing two letters nevertheless activate the intended word's lexical representation. (Perea et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Furthermore, distortions in a word's overall structure do not significantly impair reading until important visual cues, such as the relative size of lowercase letters, are altered (Smith et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1969\u003c/span\u003e). These findings corroborate the \"whole word\" recognition method, which prioritizes the perception of distinct visual configurations above individual letter-by-letter analysis (Smith, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1969\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe visual span, or the spatial area where letters can be recognised without eye movements, affects how well visual word recognition works. This perceptual window is expanded by lexical and supra-lexical information improving improves reading efficiency (Veldre et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). There are two main ways in which this expansion takes place. First, as readers depend on positional regularities to support early stages of word recognition, being familiar with word-initial letter sequences promotes quick lexical access and enhances foveal processing (Lima \u0026amp; Inhoff, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). These lexical representations not only help readers recognize the currently fixated word, but they also facilitate the extraction of parafoveal information, which allows them to start processing incoming words prior to direct fixation (Veldre \u0026amp; Andrews, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Second, compared to single vowels or clusters of consonants, orthographic rimes function as more dependable perceptual units with faster reading rates and increased identification accuracy are facilitated by their consistency (Treiman et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1995\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWord recognition is significantly impacted by the location of letter transpositions as the differences are most noticeable when transpositions take place close to the start of a word. This illustrates how a word's beginning letters have a greater impact on lexical access even when there is no parafoveal preview (White et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Transposed letter non-words often exhibit measurable behavioural impacts because of their remarkable perceptual similarity to actual words. In lexical judgment tests, such non-words are far more challenging to reject than substitution non-words. The findings are similar across phrase contexts, with a transposed letter word generating more lexical activation than a substitute word (Mirault \u0026amp; Grainger, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOrthographic coding involves several paths for processing letter identity and location. While letter identity recognition is quite rigid, letter position coding is rather flexible (Hasen\u0026auml;cker \u0026amp; Schroeder, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This adaptability is obvious in transposed-letter effects, where non-words produced by transposing internal letters can activate the semantic representation of their base words nearly as efficiently as accurately written primes. In contrast, substitution non-words lack comparable priming effects (Perea \u0026amp; Lupker, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Linguistic context controls the strength of transposed letter priming as high semantic predictability during sentence processing pre-activates certain letter identities and their positions, removing transposition effects in constraining contexts while maintaining them in neutral or non-constraining ones (Luke \u0026amp; Christianson, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Furthermore, morphological limitations limit the flexibility of transposition. Word recognition is equally disrupted by letter transpositions across morpheme divisions in inflected words as it is by whole letter substitutions (Luke \u0026amp; Christianson, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eLexical and orthographic processing are significantly impacted by changes in visual formatting. For example, differences in letter case between upper and lower case have a greater impact on word recognition within a word, than between words since case variations within words decrease reading effectiveness (Bowey, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Fournet et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Colour also has varied impacts: while it helps with visual grouping and segmentation (Pinna \u0026amp; Deiana, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), adjustments like syllable-specific colouring or contrast shifts diminish, but not eliminate, transposed-letter effects. This shows that, even in the presence of visual noise, abstract orthographic representations continue to impact position coding (Marcet et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Furthermore, colour preferences introduce processing asymmetries: pseudowords are recognized faster when presented in evolutionarily salient colours such as blue or red, whereas real words demonstrated processing advantages in green independent of valence, demonstrating an association between automatic colour processing and higher-order lexical access (Bortolotti et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003edeveloped Signal Detection Theory (SDT), a mathematical framework particularly beneficial for the evaluation of perceptual thresholds in word recognition because it provides a reliable approach for evaluating an individual's sensitivity to detecting signals, such as words, in the presence of background noise. The assumption is based on an analysis of decision-making under uncertainty, specifically yes/no tasks with a mix of signal and noise trials. In these tasks, responses are dictated by a decision variable, and the outcome, whether a participant detects the presence or absence of a signal, depends on whether this variable exceeds a predetermined criterion.\u003c/p\u003e\u003cp\u003eWhile the findings of research into transposition, priming, and orthography have been consistent, significant methodological constraints remain. A research gap exists as most studies have focused on isolated factors such as priming, transposition, or signal-based cues like colour or letter case. To address this gap, the present study employs an innovative multi-series approach that investigates how Gestalt-based holistic processing and semantic mechanisms jointly influence visual word perception. We test whether words can be distinguished from signal-based noise such as transposed, altered, or coloured variant, using Signal Detection Theory. We hypothesize that whole-word perception would be resilient to positional changes if there were minimal variation in detection rates or reading times between conditions. Therefore, as proposed by the Cambridge effect, we directly evaluate whether English word recognition functions holistically, irrespective of internal letter order or remains significantly affected by font colour and letter position.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eResearch Design:\u003c/h2\u003e\u003cp\u003eThe present study undertook a quantitative experimental design with a within sample approach to assess repeated measures. The study seeks to identify how the participants are able to respond to various stimuli and are they able to distinguish it within themselves.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eResearch Question:\u003c/h3\u003e\n\u003cp\u003eTo what extent does the visual recognition and discrimination capability in English-speaking individuals influence their overall experience in terms of reading comprehension, ease differentiating textual features, and their ability to detect signals within written materials?\u003c/p\u003e\n\u003ch3\u003eObjectives:\u003c/h3\u003e\n\u003cp\u003eTo assess the presence of difference in detection and bias between uncoloured words and coloured words.\u003c/p\u003e\u003cp\u003eTo assess the presence of difference in detection and bias between uncoloured words and words whose first letters are interchanged.\u003c/p\u003e\u003cp\u003eTo assess the presence of difference in detection and bias between uncoloured words and words whose last letters are interchanged.\u003c/p\u003e\n\u003ch3\u003eSample:\u003c/h3\u003e\n\u003cp\u003eFollowing G*Power analysis, a sample size of 33 participants residing in Bangalore city was determined (α\u0026thinsp;=\u0026thinsp;0.05, expected effect size\u0026thinsp;=\u0026thinsp;0.5, Power\u0026thinsp;=\u0026thinsp;0.75, n\u0026thinsp;=\u0026thinsp;32). The participants were postgraduate students enrolled full-time in English-medium courses to assure proficiency in both written and verbal comprehension of the English language, so reducing any confounding factors. Purposive sampling was used to identify participants, owing to its ease and efficiency in recruiting people from a specified demographic.\u003c/p\u003e\n\u003ch3\u003eInclusion Criteria:\u003c/h3\u003e\n\u003cp\u003eParticipants must to be enrolled full-time in an educational program at the point of time.\u003c/p\u003e\u003cp\u003eParticipants should possess education from an English-medium school.\u003c/p\u003e\u003cp\u003eParticipants had to have studied English as their first language since the first grade.\u003c/p\u003e\u003cp\u003eParticipation is contingent upon having normal or corrected-to-normal eyesight.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eExclusion Criteria:\u003c/h2\u003e\u003cp\u003eParticipants diagnosed with language-related difficulties or disorders as reading challenges may affect test results\u003c/p\u003e\u003cp\u003eParticipants with any diagnosed learning disorders.\u003c/p\u003e\u003cp\u003eParticipants diagnosed with neurological or neurodevelopmental disorders, including a history of childhood seizures.\u003c/p\u003e\u003cp\u003eParticipants with colour blindness.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStatistical Techniques:\u003c/h3\u003e\n\u003cp\u003eThe signal detection theory was used to score the responses. The sensitivity index d' was measured using the formula: d'=Z (Hit Rate)- Z (False Alarm Rate) adjusting for extreme values as per corrections recommended by (Hautus, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). Group differences were assessed using Friedman's test, and pairwise differences were evaluated post-hoc using the Wilcoxon signed rank test. The analysis was conducted using R Studio and SPSS.\u003c/p\u003e\n\u003ch3\u003eProcedure:\u003c/h3\u003e\n\u003cp\u003eThe participants were instructed to identify words presented on a screen, some of which were correctly spelled while others had jumbled letters. Participants were asked to press \"A\" if they perceived the word as correctly spelled and \"L\" if they thought otherwise. After confirming understanding, the task began. Words were presented on a separate screen measuring 20 cm x 32 cm, using Arial font size 32. Participants sat approximately 2.5 feet from the screen. Their responses were recorded and exported into a CSV file.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eStimuli:\u003c/h2\u003e\u003cp\u003eThe stimulus set comprised 126 words, carefully chosen to reflect common language usage in India. Each category included 22 words, distributed across word lengths from three to eight letters. Categories varied based on word appearance: Category 1 contained uncoloured normal words, Category 2 had uncoloured words with transposed letters, Category 3 presented normal words in colour, and Category 4 featured coloured words with transposed letters. Categories 5 and 6 included words with initial and final letters jumbled, respectively. This systematic approach allowed for a thorough investigation into word processing under different conditions targeting cognitive processes involved in word recognition.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eProbabilities of hits and false alarm rates in detection and bias\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePairs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eCondition\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eProbabilities\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSignal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNoise\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHits\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eFalse Alarm\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003ed'\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003ec\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePair 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUncoloured Transposed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUncoloured Untransposed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e1.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePair 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eColoured Transposed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eColoured Untransposed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e1.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePair 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAltered Beginning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUncoloured Untransposed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e2.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePair 4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAltered\u003c/p\u003e\u003cp\u003eEnding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUncoloured Untransposed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e1.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe study was conducted on a sample on 33 postgraduate students (5 males and 28 females) with a mean age of 21.5 years. The data from each stimulus category was grouped in pairs in order to collect the sensitivity index and response bias. In Pair 1, the participants consistently displayed the capacity to distinguish signal from noise with low response bias, creating a baseline for comparison. Pair 2 showed a slight increase in sensitivity; however, this was accompanied by a shift toward a more liberal decision threshold, implying that the inclusion of colour may have influenced participants to adopt a more affirmative response tendency. Pair 3 generated the highest level of sensitivity, demonstrating that transpositions affecting the first letters of words were most noticeable and easy to identify. In contrast, Pair 4 had lower sensitivity and a more moderate response bias, indicating that end-letter modifications were less perceptually disruptive. These data indicate that both visual prominence e.g., colour and structural position of modifications at the beginning or ending influence detection accuracy and reaction tendencies in visual word recognition tasks.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFriedman test for group differences between pairs in d' and c\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeasure\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChi-Square\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAssymp. Sig.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eKendall\u0026rsquo;s W\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ed'\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.938\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.232\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ec\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.577\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.228\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eA Friedman test was used to determine if sensitivity index d\u0026prime; and response bias c differed substantially across the four experimental conditions. The pairs in the measure of sensitivity index yielded a weak effect size indicating an approximate 23% of variance (χ\u0026sup2;=22.938, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, the response bias showed a significant but weak effect size indicating an approximate 22% of variance between the pairs (χ\u0026sup2;=22.577, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePost-hoc Wilcoxon signed rank test for pair wise differences\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeasure\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eComparison\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAsymp. Sig.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003er\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003ed'\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePair 2 X Pair 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.308\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.177\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePair 3 X Pair 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-3.755\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.653\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePair 4 X Pair 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.230\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.219\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.214\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003ec\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePair 2 X Pair 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.470\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePair 3 X Pair 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-3.756\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.653\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePair 4 X Pair 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.253\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.210\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.218\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTo determine the specific condition differences that contributed to the significant Friedman test results, post hoc pairwise comparisons using the Wilcoxon Signed-Rank test were carried out. A statistically significant difference was identified between Pair 3 altered beginning and Pair 1 uncoloured transposed (Z=-3.755, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, r= -0.653) indicating a substantially higher level of sensitivity when alterations occurred at the beginning of words. Comparisons between Pair 2 coloured transposed and Pair 1 uncoloured transposed (Z = \u0026minus;\u0026thinsp;1.02, p\u0026thinsp;=\u0026thinsp;.308), and between Pair 4 altered ending and Pair 1 uncoloured transposed (Z = \u0026minus;\u0026thinsp;1.23, p\u0026thinsp;=\u0026thinsp;.219), did not reach statistical significance, suggesting that these conditions did not have differences in detection performance compared to the baseline.\u003c/p\u003e\u003cp\u003eSignificant differences in response bias were observed between Pair 2 coloured transposed and Pair 1 (Z = -2.70, p\u0026thinsp;=\u0026thinsp;.006, r = -0.470) and between Pair 3 altered beginning and Pair 1 (Z = -3.76, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, r = -0.653), indicating a shift towards a more liberal response criterion when color transpositions or initial letter alterations were introduced. The comparison of Pair 4 and Pair 1 (Z = -1.25, p\u0026thinsp;=\u0026thinsp;.210, r = -0.218) yielded no statistically significant difference, suggesting that changes in endings had little effect on response thresholds. The findings demonstrated structural and visual modifications have varied effects on perceptual sensitivity and detection processes, with initial letter adjustments and coloured transpositions having the greatest influence across both measures.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe study used signal detection theory (SDT) to investigate how orthographic and perceptual changes, especially color, initial-letter transposition, and terminal-letter transposition, affect visual word identification. Thirty-three postgraduate students completed detection tasks in four different within-subject conditions ie baseline transposed letters without color, color-enhanced transpositions, initial-letter changes, and final-letter alterations. The results indicated a statistically significant impacts in sensitivity and response bias best explain how visual salience and structural disruption influence reading processes.\u003c/p\u003e\u003cp\u003eThe predominance of first letters in visual word identification relates to the well-known fact that the primary letters of a word is processed more effectively and plays an important part in recognizing the word. Research repeatedly demonstrates a significant advantage for the first letter position, most likely due to quick spatial attention deployment to the start of the word. Multiple trials indicate that the beginning letter of a word is identified more precisely and rapidly than other locations, even after accounting for visual matching and decision processes. This impact is consistent across word orientations ie horizontal and vertical and is not explained by simple perceptual matching or post-perceptual choice techniques. Instead of serial processing or decision biases, the beneficial effect is associated with a rapid, automatic allocation of spatial attention to the word's beginning once it occurs (Aschenbrenner et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAdvanced temporal sampling investigations reveal that, while all letter positions are processed concurrently, each position, including the first, has different temporal processing characteristics. This indicates that the first letter isn't processed in strict serial sequence, but it nonetheless sticks out owing to distinct attentional or perception mechanisms (Arguin \u0026amp; Fortier St-Pierre, 2023). The unique processing of each letter location lends credence to the notion that the beginning letter's dominance stems from both parallel processing and position-specific attentional effects (Arguin \u0026amp; Fortier-St-Pierre, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Aschenbrenner et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The influence of orthographic neighbors - words that vary by one letter, varies by letter position, with the initial letter frequently being more informative and influential in word identification tests (Luthra et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFlexible orthographic coding is the brain's capacity to recognize words even when the order of letters or syllables is changed, a feature that is frequently researched using transposition effects. This flexibility is essential for efficient reading and is influenced by both the features of writing systems and reading experiences. Readers frequently misinterpret words with transposed internal letters e.g., \"jugde\" for \"judge\", implying that letter position is conveyed flexibly rather than rigorously. This effect is evident early in reading development and extends throughout adulthood, notably for letter strings compared to non-letter strings, indicating that a specific mechanism for letter position coding develops with reading experience (Hasen\u0026auml;cker \u0026amp; Schroeder, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Massol et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe extent of flexibility in letter position encoding varies by language and script. Korean Hangul and Chinese exhibit both similarities and variations in transposition effects, which are impacted by script construction and word proximity (Z. Liu et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). People with great orthographic competence, such as Scrabble players, had less transposed-letter effects, showing that experience can influence letter position coding (Perea et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Models such as open-bigram representations and neurological evidence support the notion that letter position coding is both adaptable and specialised. Recognition memory and reading experiments support the open-bigram hypothesis, which proposes that the brain encodes not just individual letters but also pairs of letters in any sequence, hence explaining the observed flexibility (Zhang \u0026amp; Osth, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Visual perception features e.g., color and contrast can alter but not remove transposition effects, emphasizing both perceptual and abstract orthographic components (Marcet et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSpatial attention has a substantial impact on how terminal letters are processed in word recognition. Directing spatial attention to certain letter locations, particularly at the beginning of a word, improves identification accuracy and lowers mistakes, with the first letter benefiting the most from attentional concentration. Terminal-letter positions have a distinct function in visual word recognition, although their influence is not necessarily dominating, restricted, or context-dependent. Endogenous attention, when focused on a specific letter position, is more beneficial than reflexive or exogenous. Endogenous signals are highly effective in reducing mistakes caused by letters being confused for one another, particularly in packed or complicated letter strings. Valid spatial cues particularly endogenous ones minimize position swap mistakes, which occur when a letter is reported from the incorrect place, more efficiently than misidentification errors. This shows that spatial attention aids in the maintenance of precise letter order, which is required for accurate word recognition (Ramamurthy et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003eb\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePredictive coding models suggest that the brain pre-activates orthographic and lexical-semantic representations before a word appears, especially in predictable contexts. This pre-activation sharpens neural responses, making word recognition more efficient. Neuroimaging and electrophysiological research have shown context-based facilitation occurs in many stages. Early impacts appear in visual and orthographic processing regions, whereas later effects are associated with lexical-semantic processing. Top-down feedback from higher-level lexical regions can influence early word form processing, enabling interactive rather than simply feedforward models (Kim \u0026amp; Lai, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Y. Liu et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eLexical expectations, influenced by context, improve identification of common words and those with strong semantic connotations (Eisenhauer et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, complete prediction of precise word forms is uncommon, with the brain frequently anticipating semantic or morpho-syntactic elements, which aids reading (Luke \u0026amp; Christianson, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Lexical expectations can impair identification of non-words, highlighting the distinctiveness of predictive facilitation for real words (Hendrix \u0026amp; Sun, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe ramifications of initial-letter primacy and colour effects are significant in education, design, and assistive technology. Enhancing starting letters with typographic emphasis or color may improve reading accuracy and fluency, as observed in therapies for dyslexia and early readers. For user-interface designers, increasing visual salience in textual displays can boost user confidence without affecting interpretability. These findings show how cognitive research may directly influence real-world practice.\u003c/p\u003e\u003cp\u003eThe limited, homogeneous sample of just postgraduate students is one of the study's drawbacks. Future study should include more diverse populations, such as children and those with reading difficulties. Integrating reaction-time measurements or neurophysiological recordings such as EEG/ERP and eye-tracking might reveal the temporal dynamics of letter-position effects. Manipulating color signals more systematically, varying hue intensity, background contrast, or spatial placement could reveal their impact on response bias. Finally, cross-linguistic replication is required, particularly in scripts with non-left-to-right orientation, to evaluate whether the initial-letter advantage is consistent across orthographies.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eWe used signal detection theory to investigate how structural and perceptual modifications, especially color, initial-letter, and end-letter adjustments, affect visual word identification. The findings showed that initial-letter transpositions significantly raised sensitivity and altered response bias, emphasizing the importance of word-onset in lexical access. Colour impacted decisional criteria without improving detection, but end-letter alterations had no effect. The findings provide evidence for variable orthographic coding as well as the impact of visual salience on recognition processes, helping to understand how attentional and structural elements influence reading.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting Interests:\u003c/h2\u003e\n\u003cp\u003eThe authors have no competing or conflict of interests to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll ethical guidelines were adhered to during the conduction of the study. Informed consent was obtained from all the participants prior to the conduction of the experiment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData and Materials availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data may be availed based on reasonable request from the Corresponding Author\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eNo funds, grants, or other support was received for the present study.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eHCR: Conceptualization, conducting experiment, writing manuscript first draft, reviewing manuscript; FF: Conceptualization, conducting experiment, reviewing manuscript; LL: Supervision, Conceptualization, reviewing manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eThe authors acknowledge the assistance of Mr Shreyas Mallya.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eArguin, M., \u0026amp; Fortier-St-Pierre, S. 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Modelling orthographic similarity effects in recognition memory reveals support for open bigram representations of letter coding. \u003cem\u003eCognitive Psychology\u003c/em\u003e, \u003cem\u003e148\u003c/em\u003e, 101619. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/J.COGPSYCH.2023.101619\u003c/span\u003e\u003cspan address=\"10.1016/J.COGPSYCH.2023.101619\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Word Recognition, Language Processing, Psycholinguistics, Signal Detection, Transposition","lastPublishedDoi":"10.21203/rs.3.rs-7292889/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7292889/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe Cambridge effect describes the ability to recognize words despite alteration or transposition of letters within. In the study we investigate how holistic visual signals, such as overall word form and initial-letter prominence, impact reading accuracy. A sample of 33 postgraduate students took part in a signal detection task with four word-pair conditions: uncoloured transposed, coloured transposed, altered starting, and altered ending. Signal Detection Theory was used to quantify perceptual discrimination by measuring sensitivity (d\u0026prime;) and response bias (c). Results revealed enhanced sensitivity for words with initial-letter changes and a liberal response bias when colour was introduced, whereas end-letter modifications had minimal impact. These results emphasize the importance of word-initial letters and the modulatory impact of visual salience in reading processes. Flexible orthographic coding, visual attention and structural elements are crucial to word recognition. Implications include education, technology, psychology, and therapeutic applications, emphasising the difficulties of reading comprehension as well as the need of sequential and holistic perception theories. Future research could explore combined stimuli impacts and cross-language processes for enhanced understanding with the simultaneous use of neuroimaging techniques.\u003c/p\u003e","manuscriptTitle":"Visual Salience and Orthographic Word Processing in Reading and Recognition: A Signal Detection Approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-21 07:39:41","doi":"10.21203/rs.3.rs-7292889/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"164bb99a-e349-4727-9401-dbb38ab8938e","owner":[],"postedDate":"August 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-10T13:08:33+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-21 07:39:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7292889","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7292889","identity":"rs-7292889","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}