Lexical-Decision Task – Visual Word Recognition Kit
Zefwih
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Ready-to-run lexical decision task - masked priming, Go/No-Go, auto stats, full CSV logging - to identify whether letter combinations constitute real words.The lexical decision task (LDT), introduced by Meyer and Schvaneveldt in the 1970s, requires participants to identify whether letter combinations constitute real English words. For instance, recognizing "GIRL" as a word but dismissing "XLFFE" as non-word. This task was developed to explore the organization and retrieval of information from long-term memory. The seminal study revealed quicker responses to semantically related words, indicating that reading a word primes the recognition of related words. Currently, the LDT is widely used in psychology and psycholinguistics, with numerous variations of the task existing.A complete, ready-to-run implementation of the lexical decision task — the standard chronometric method of visual word recognition research (Meyer & Schvaneveldt, 1971). Drop a prefab into your scene, press Play, and you have a scientifically valid, data-logging word recognition experiment.Everything runs from one script and one mode-aware Inspector. No coding is required to use, customise or extend any variant.5 scientific paradigms, one component:Standard Yes/No — the classic reference protocolGo / No-Go — single-key responding, faster and more accurate (Perea, Rosa & Gómez, 2002)Semantic Priming — visible prime before each targetMasked Priming — the Forster & Davis sandwich procedure, with a subliminal 50 ms primeDouble / Two-String — the original Meyer & Schvaneveldt paired design3 stimulus modalities: on-screen text, sprites, or spoken audio with onset/offset reaction times.Statistics computed automatically — no post-processing needed to see your effect:Accuracy, errors, timeouts; mean, SD, median, skewness, kurtosis of reaction timesLexicality effect, priming effect and word frequency effectSignal detection analysis with d' and criterion cInverse efficiency score, plus breakdowns by lexical class, condition label and prime conditionFully customisable, out of the box:Your own word list via a simple text table — or use the three included example setsResponse keys, one-click counterbalancing, timing, trial and block countsEvery instruction screen editable, so the task is translated without touching codeColors, fonts, fixation symbol, upper-case renderingOne-click toggles for the progress overlay, the key legend and the feedback textSuitable for:Academic research and student projects in psychology, linguistics and cognitive scienceClinical and educational screening of reading and word recognitionBrain-training and language-learning applicationsAny project that needs a validated, science-grounded word recognition benchmark10 ready-made variants, all built from a single master canvas — switching between them is an Inspector change, never a rebuild.Requirements and dependencies:Unity 2022.3 LTS or newer.TextMeshPro, installed through the Unity Package Manager. It ships with the Unity Editor and is not included in this package. In Unity 6 its functionality is part of the UGUI package and no separate installation is needed.Active Input Handling set to "Input Manager (Old)" or "Both" in the Player settings. The task reads the keyboard through the legacy Input Manager.Optional, for VR only: the SteamVR Unity Plugin (free, by Valve) plus the scripting define symbol STEAMVR_ENABLED. The plugin is not included in this package. Without it the VR code compiles out completely and the task runs normally on the keyboard — nothing else is affected.Nothing else. No third-party library, font, image, sound or word-frequency norm database is required, and none is bundled. See the Third-Party Notices file in the package.For further reading, see:Meyer, D. E., & Schvaneveldt, R. W. (1971). Facilitation in recognizing pairs of words: Evidence of a dependence between retrieval operations. Journal of Experimental Psychology, 90, 227-234.Balota, D. A., Yap, M. J., Cortese, M. J., Hutchison, K. A., Kessler, B., Loftis, B., et al. (2007). The english lexicon project. Behavior Research Methods, 39 (3), 445-459.We are always interested in scientific collaborations. Please reach out to contact@zefwih.com5 task modes: Standard Yes/No, Go / No-Go, Primed, Masked Priming, Double / Two-String3 stimulus modalities: Visual Text, Visual Image (Sprite), Auditory with selectable onset/offset RT reference4 nonword classes: pseudowords, illegal letter strings and pseudohomophones, selectable per session as an experimental manipulation10 ready-made prefabs, 6 with their own example scene, all variants of one master canvasAutomatic statistics: accuracy, mean, SD, median, skewness, kurtosis, inverse efficiency, lexicality effect, priming effect, condition effect, plus d' and criterion c with log-linear correctionFull data logging: 27-column per-trial CSV with escaped cells, plus a human-readable session summary, written automaticallyFlexible stimulus input: TextAsset table, external file at runtime, inline Inspector lists, or built-in demo stimuli; semicolon, tab or comma separatedBalanced trial generation: configurable word/nonword ratio, sampling with or without replacement, run-length control, reproducible random seedOne-click counterbalancing: swaps the response keys and updates instructions and key legend automaticallyMaster-prefab design: one canvas serves every variant; the script activates exactly the right elements at runtime4 UnityEvents (trial / block / session, plus a no-argument session event) for integration without touching the scriptOptional VR support: SteamVR controller input alongside the keyboardIncluded EditMode & PlayMode automated testsRequires: Unity 2022.3 LTS+, TextMeshPro, Active Input Handling = "Input Manager (Old)" or "Both"
