Name: lexical decision task for studying written word recognition in adults with and without dementia or mild cognitive impairment
Uploaded: 2019-06-25T14:30:00
Description: Watch this Scientific Journal Video about Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment at JoVE.com

We thank Minna Lehtonen, Tuomo H&#228;nninen, Merja Hallikainen, and Hilkka Soininen for their contribution to the data collection and processing reported here. The data collection was supported by VPH Dementia Research enabled by EU, Grant agreement No. 601055.

The protocol follows the guidelines of the Ethics Committee of the Hospital District of Northern Savo (IRB00006251).
1. Participant screening
<ol>
	<li>Recruit younger and older adults who have&#160;normal or corrected-to-normal vision and are native speakers of the language tested unless the study addresses specific research questions regarding second language acquisition.</li>
	<li>For healthy control groups, exclude participants who have a history of neurological or psychiatric disorders....

<ol>
	<li>Bybee, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=From+Usage+to+Grammar:+The+Mind's+Response+to+Repetition.">From Usage to Grammar: The Mind's Response to Repetition.</a> Language. 82 (4), 711-733 (2006).</li><li>Oldfield, R. C., Wingfield, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Response+latencies+in+naming+objects.">Response latencies in naming objects.</a> The Quarterly Journal of Experimental Psychology. 17, 273-281 (1965).</li><li>Nikolaev, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+morphological+family+on+word+recognition+in+normal+aging,+mild+cognitive+impairment,+and+Alzheimer&#8217;s+disease.">Effects of morphological family on word recognition in normal aging, mild cognitive impairment, and Alzheimer&#8217;s disease.</a> Cortex. 116, 91-103 (2019).</li><li>Milin, P., Feldman, L. B., Ramscar, M., Hendrix, P., Baayen, R. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Discrimination+in+lexical+decision.">Discrimination in lexical decision.</a> PLoS ONE. 12 (2), 1-42 (2017).</li><li>Andrews, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Frequency+and+neighborhood+size+effects+on+lexical+access:+activation+or+search?.">Frequency and neighborhood size effects on lexical access: activation or search?.</a> Journal of Experimental Psychology: Learning, Memory, and Cognition. 15, 802-814 (1989).</li><li>Grainger, J., Muneaux, M., Farioli, F., Ziegler, J. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+phonological+and+orthographic+neighbourhood+density+interact+in+visual+word+recognition.">Effects of phonological and orthographic neighbourhood density interact in visual word recognition.</a> The Quarterly Journal of Experimental Psychology. 58 (6), 981-998 (2005).</li><li>Ossher, L., Flegal, K. E., Lustig, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Everyday+memory+errors+in+older+adults.">Everyday memory errors in older adults.</a> Aging, Neuropsychology, and Cognition. 20, 220-242 (2013).</li><li>Barresi, B. A., Nicholas, M., Connor, L. T., Obler, L. K., Albert, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Semantic+degradation+and+lexical+access+in+age-related+naming+failures.">Semantic degradation and lexical access in age-related naming failures.</a> Aging, Neuropsychology, and Cognition. 7, 169-178 (2000).</li><li>Chertkow, H., Whatmough, C., Saumier, D., Duong, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cognitive+neuroscience+studies+of+semantic+memory+in+Alzheimer's+disease.">Cognitive neuroscience studies of semantic memory in Alzheimer's disease.</a> Progress in Brain Research. 169, 393-407 (2008).</li><li>Cuetos, F., Arce, N., Mart&#237;nez, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Word+recognition+in+Alzheimers&#8217;s+disease:+Effects+of+semantic+degeneration.">Word recognition in Alzheimers&#8217;s disease: Effects of semantic degeneration.</a> Journal of Neuropsychology. 11, 26-39 (2015).</li><li>Stilwell, B. L., Dow, R. M., Lamers, C., Woods, R. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Language+changes+in+bilingual+individuals+with+Alzheimer&#8217;s+disease.">Language changes in bilingual individuals with Alzheimer&#8217;s disease.</a> International Journal of Language &amp; Communication Disorders. 51, 113-127 (2016).</li><li>Obler, L. K., Segalowitz, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Language+and+brain+dysfunction+in+dementia.">Language and brain dysfunction in dementia.</a> Language functions and brain organization. , 267-282 (1983).</li><li>Obler, L. K., Albert, M. L., Sarno, M. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Language+in+the+elderly+aphasic+and+in+the+demented+patient.">Language in the elderly aphasic and in the demented patient.</a> Acquired aphasia. , 385-398 (1981).</li><li>Obler, L. K., Gjerlow, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Language and the brain. , (1999).</li><li>McKhann, G. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+diagnosis+of+dementia+due+to+Alzheimer&#8217;s+disease:+Recommendations+from+the+National+Institute+on+Aging+-+Alzheimer&#8217;s+Association+workgroups+on+diagnostic+guidelines+for+Alzheimer&#8217;s+disease.">The diagnosis of dementia due to Alzheimer&#8217;s disease: Recommendations from the National Institute on Aging - Alzheimer&#8217;s Association workgroups on diagnostic guidelines for Alzheimer&#8217;s disease.</a> Alzheimer&#8217;s Dementia. 7, 263-269 (2011).</li><li>Winblad, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mild+cognitive+impairment+-+beyond+controversies,+towards+a+consensus:+Report+of+the+International+Working+Group+on+Mild+Cognitive+Impairment.">Mild cognitive impairment - beyond controversies, towards a consensus: Report of the International Working Group on Mild Cognitive Impairment.</a> Journal of Internal Medicine. 256, 240-246 (2004).</li><li>Albert, M. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+diagnosis+of+mild+cognitive+impairment+due+to+Alzheimer&#8217;s+disease:+Recommendations+from+the+National+Institute+on+Aging+-+Alzheimer&#8217;s+Association+workgroups+on+diagnostic+guidelines+for+Alzheimer&#8217;s+disease.">The diagnosis of mild cognitive impairment due to Alzheimer&#8217;s disease: Recommendations from the National Institute on Aging - Alzheimer&#8217;s Association workgroups on diagnostic guidelines for Alzheimer&#8217;s disease.</a> Alzheimer&#8217;s &#38; Dementia: The Journal of the Alzheimer&#8217;s Association. 7, 270-279 (2011).</li><li>Hughes, C. P., Berg, L., Danziger, W. L., Coben, L. A., Martin, R. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+new+clinical+scale+for+the+staging+of+dementia.">A new clinical scale for the staging of dementia.</a> The British Journal of Psychiatry. 140, 566-572 (1982).</li><li>Baayen, R. H., Cutler, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Data+Mining+at+the+Intersection+of+Psychology+and+Linguistics.">Data Mining at the Intersection of Psychology and Linguistics.</a> Twenty-first century psycholinguistics: Four cornerstones. , 69-83 (2005).</li><li>Brants, T., Franz, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Web 1T 5-gram, version 1. , (2006).</li><li>Baayen, R. H., Piepenbrock, R., Gulikers, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The CELEX lexical database (CD-ROM). , (1995).</li><li>Wagenmakers, E. J., Ratcliff, R., Gomez, P., McKoon, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+diffusion+model+account+of+criterion+shifts+in+the+lexical+decision+task.">A diffusion model account of criterion shifts in the lexical decision task.</a> Journal of Memory and Language. 58, 140-159 (2008).</li><li>Dufau, S., Grainger, J., Ziegler, J. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=How+to+say+&#8220;no&#8221;+to+a+non-word:+a+leaky+competing+accumulator+model+of+lexical+decision.">How to say &#8220;no&#8221; to a non-word: a leaky competing accumulator model of lexical decision.</a> Journal of Experimental Psychology: Learning, Memory, and Cognition. 38, 1117-1128 (2012).</li><li>R Core Team. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> R: A language and environment for statistical computing. , (2018).</li><li>Venables, W. N., Ripley, B. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Modern applied statistics with S. , (2002).</li><li>Baayen, R. H., Milin, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analyzing+reaction+times.">Analyzing reaction times.</a> International Journal of Psychological Research. 3 (2), 12-28 (2010).</li><li>Koller, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=robustlmm:+An+R+package+for+robust+estimation+of+linear+mixed-effects+models.">robustlmm: An R package for robust estimation of linear mixed-effects models.</a> Journal of Statistical Software. 75 (6), 1-24 (2016).</li><li>Bates, D., M&#228;chler, M., Bolker, B., Walker, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fitting+Linear+Mixed-Effects+Models+Using+lme4.">Fitting Linear Mixed-Effects Models Using lme4.</a> Journal of Statistical Software. 67, 1-48 (2015).</li><li>Kuznetsova, A., Brockhoff, P. B., Christensen, R. H. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=lmerTest+Package:+Tests+in+Linear+Mixed+Effects+Models.">lmerTest Package: Tests in Linear Mixed Effects Models.</a> Journal of Statistical Software. 82, 1-26 (2017).</li><li>Akaike, H., Petrov, B. N., Csaki, B. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Information+theory+and+an+extension+of+the+maximum+likelihood+principle.">Information theory and an extension of the maximum likelihood principle.</a> Second International Symposium on Information Theory. , 267-281 (1973).</li><li>Sakamoto, Y., Ishiguro, M., Kitagawa, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Akaike Information Criterion Statistics. , (1986).</li><li>Barr, D. J., Levy, R., Scheepers, C., Tily, H. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Random+effects+structure+for+confirmatory+hypothesis+testing:+Keep+it+maximal.">Random effects structure for confirmatory hypothesis testing: Keep it maximal.</a> Journal of Memory and Language. 68, 255-278 (2013).</li><li>Bates, D., Kliegl, R., Vasishth, S., Baayen, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Parsimonious+mixed+models.">Parsimonious mixed models.</a> arXiv:1506.04967v2. , (2015).</li><li>Harrison, X. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Brief+introduction+to+mixed+effects+modelling+and+multi-model+inference+in+ecology.">Brief introduction to mixed effects modelling and multi-model inference in ecology.</a> PeerJ. 6, 1-32 (2018).</li><li>Kimball, A. E., Shantz, K., Eager, C., Roy, C. E. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Confronting+quasi-separation+in+logistic+mixed+effects+for+linguistic+data:+a+Bayesian+approach.">Confronting quasi-separation in logistic mixed effects for linguistic data: a Bayesian approach.</a> Journal of Quantitative Linguistics. , (2018).</li><li>Coltheart, M., Davelaar, E., Jonasson, J. T., Besner, D., Dornick, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Access+to+the+internal+lexicon.">Access to the internal lexicon.</a> Attention and performance, vol. VI. , 535-556 (1977).</li><li>Caselli, N. K., Caselli, M. K., Cohen-Goldberg, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Inflected+words+in+production:+Evidence+for+a+morphologically+rich+lexicon.">Inflected words in production: Evidence for a morphologically rich lexicon.</a> The Quarterly Journal of Experimental Psychology. 69, 432-454 (2016).</li><li>Yarkoni, T., Balota, D., Yap, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Moving+beyond+Coltheart&#8217;s+N:+A+new+measure+of+orthographic+similarity.">Moving beyond Coltheart&#8217;s N: A new measure of orthographic similarity.</a> Psychonomic Bulletin &amp; Review. 15 (5), 971-979 (2008).</li><li>Cohen, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Recognition+and+retrieval+of+proper+names:+Age+differences+in+the+fan+effect.">Recognition and retrieval of proper names: Age differences in the fan effect.</a> European Journal of Cognitive Psychology. 2 (3), 193-204 (1990).</li><li>Kemmerer, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Cognitive neuroscience of language. , (2015).</li><li>Baayen, R. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Analyzing linguistic data: A practical introduction to statistics using R. , (2008).</li><li>Nikolaev, A., Lehtonen, M., Higby, E., Hyun, J., Ashaie, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+facilitatory+effect+of+rich+stem+allomorphy+but+not+inflectional+productivity+on+single-word+recognition.">A facilitatory effect of rich stem allomorphy but not inflectional productivity on single-word recognition.</a> Applied Psycholinguistics. 39, 1221-1238 (2018).</li><li>Nikolaev, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Behavioural+and+ERP+effects+of+paradigm+complexity+on+visual+word+recognition.">Behavioural and ERP effects of paradigm complexity on visual word recognition.</a> Language, Cognition and Neuroscience. 10, 1295-1310 (2014).</li></ol>

By using a simple language task that does not require language production, the present study investigated the impact of various lexical variables on word recognition in neurologically healthy younger and older adults, as well as in people with Alzheimer&#8217;s disease or Mild Cognitive Impairment. The age range used for recruiting &#8220;older adults&#8221; might depend on the specific research interests; however, the range for the healthy elderly group should match as closely as possible the age range and distribution ...

Words are stored in the mental lexicon in a highly interconnected network. The connections between words may reflect shared properties, such as semantic similarity (e.g., dog and cat), form similarity (dog and fog), or frequent co-occurrence in common language use (e.g., dog and leash). Cognitive theories of language, such as usage-based theory1, argue that every encounter of a word by a language user has an effect on the word&#8217;s mental representation. According to Exemplar Theory, a word&#8217;s representation consists of many exemplars, which are built up from individual tokens of language use and which represent the variability that exists for a given category. The frequency of use2 impacts representations in memory by contributing to the strength of an exemplar1.
Word recognition speed can reveal the characteristics of the mental lexicon. A commonly used experimental paradigm for measuring the speed of word recognition is the lexical decision task. In this task, participants are presented with letter strings on a monitor, one at a time. They are instructed to decide as quickly as possible whether the letter string on the screen is a real word or not by pressing the corresponding button.
By examining reaction times for real words, researchers can address a number of important questions about language processing. For example, identifying which factors make recognition faster can test hypotheses about the structure of the mental lexicon and reveal its architecture. Moreover, comparisons of performance across different groups of participants can help us understand the influence of various types of language experience, or, in the case of aging or neurodegenerative diseases (e.g., Alzheimer&#8217;s disease), the role of cognitive decline.
Some factors (e.g., the frequency of use) exhibit greater influence on word recognition than other factors (e.g., word length). With advancing age, the way people recognize written words might change3,4. Younger adults tend to rely heavily on semantic (meaning-based) aspects of a word, such as how many compounds (e.g., bulldog) or derived words (e.g., doggy) share aspects of both form and meaning with the target word (in this case, dog). Word recognition for older adults appears to be more influenced by form-based aspects, such as the frequency that two subsequent letters co-occur in the language (e.g., the letter combination st occurs more often in English words than the combination sk).
To determine the factors that influence the word recognition speed across different groups, the researcher can manipulate certain variables in the stimulus set and then test the power of these variables to predict word recognition speed. For example, to test whether word recognition is driven by semantic or form-based factors, the stimulus set should include variables that reflect the degree of connectivity of a word to its semantic neighbors in the mental lexicon or its connectivity to other words that share part of its form.
This method was used in the current study to investigate whether word recognition speed is influenced by different factors in younger and older adults and in individuals with Alzheimer&#8217;s disease (AD) or mild cognitive impairment (MCI)3. The method described here is based on visual word recognition but can be adapted to the auditory modality. However, some variables that are significant predictors of reaction times in a typical visual lexical decision experiment might not predict response latencies in an auditory lexical decision or may have the opposite effect. For example, the phonological neighborhood has the opposite effect across these two modalities5: &#160;words with larger phonological neighborhoods exhibit a facilitatory effect on visual word recognition but result in longer response latencies in auditory lexical decision6.
Word-finding difficulties in older adults7 have been generally attributed to difficulty accessing the phonological word form rather than a breakdown of the semantic representation8. However, AD research has primarily focused on semantic declines9,10,11,12,13,14. It is important to disentangle how semantic and orthographic factors influence the recognition of written words in aging with and without cognitive decline. The influence of form-related factors is more pronounced in older than in younger adults, and it remains significant in people with MCI or AD3. Thus, this methodology can help us uncover features of the mental lexicon across different populations and identify changes in the lexicon&#8217;s organization with age and neuropathology. One concern when testing patients with neuropathology is that they may have difficulties accessing task-related knowledge. However, the lexical decision task is a simple task with no burden on working memory or other complex cognitive skills that many patients exhibit problems with. It has been considered appropriate for AD and MCI populations.

<table>
	<tbody>
		<tr>
			<td>E-Prime</td>
			<td>Psychology Software Tools</td>
			<td>version 2.0.10.356.</td>
			<td></td>
		</tr>
		<tr>
			<td>PC with Windows and Keyboard</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>R</td>
			<td>R Foundation for Statistical Computing</td>
			<td>R Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.</td>
			<td></td>
		</tr>
	</tbody>
</table>

lexical decision task for studying written word recognition in adults with and without dementia or mild cognitive impairment

Older adults are slower at recognizing visual objects than younger adults. The same is true for recognizing that a letter string is a real word. People with Alzheimer&#39;s disease (AD) or Mild Cognitive Impairment (MCI) demonstrate even longer responses in written word recognition than elderly controls. Despite the general tendency towards slower recognition in aging and neurocognitive disorders, certain characteristics of words influence word recognition speed regardless of age or neuropathology (e.g., a word&#8217;s frequency of use). We present here a protocol for examining the influence of lexical characteristics on word recognition response times in a simple lexical decision experiment administered to younger and older adults and people with MCI or AD. In this experiment, participants are asked to decide as quickly and accurately as possible whether a given letter string is an actual word or not. We also describe mixed-effects models and principal components analysis that can be used to detect the influence of different types of lexical variables or individual characteristics of participants on word recognition speed.

Table 1 shows a list of variables that were obtained from three different sources (a corpus, a dictionary, and pilot testing of test items) that are included in the analysis as fixed-effect predictors. Many of these variables have been previously reported to affect word recognition speed.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Corpus:</td>
			<td></td>
		</tr>
		<tr>
			<td>Base frequency</td>
			<td>the numbe...

Watch this Scientific Journal Video about Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment at JoVE.com

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

This article describes how to implement a simple lexical decision experiment to assess written word recognition in neurologically healthy participants and in individuals with dementia and cognitive decline. We also provide a detailed description of reaction time analysis using principal components analysis (PCA) and mixed-effects modeling.

Older adults are slower at recognizing visual objects than younger adults. The same is true for recognizing that a letter string is a real word. People ...

Research

JoVE Journal

Behavior

The Crossmodal Congruency Task as a Means to Obtain an Objective Behavioral Measure in the Rubber Hand Illusion Paradigm

The rubber hand illusion (RHI) is a popular experimental paradigm. Participants view touch on an artificial rubber hand while the participants' own hidden ...

Uncovering Beat Deafness: Detecting Rhythm Disorders with Synchronized Finger Tapping and Perceptual Timing Tasks

A set of behavioral tasks for assessing perceptual and sensorimotor timing abilities in the general population (i.e., non-musicians) is presented here ...

Transferring Cognitive Tasks Between Brain Imaging Modalities: Implications for Task Design and Results Interpretation in fMRI Studies

As cognitive neuroscience methods develop, established experimental tasks are used with emerging brain imaging modalities. Here transferring a paradigm ...

The Attentional Set Shifting Task: A Measure of Cognitive Flexibility in Mice

Cognitive impairment, particularly involving dysfunction of circuitry within the prefrontal cortex (PFC), represents a core feature of many ...

The Emotional Stroop Task: Assessing Cognitive Performance under Exposure to Emotional Content

The emotional Stroop effect (ESE) is the result of longer naming latencies to ink colors of emotion words than to ink colors of neutral words. The ...

Comparing the Frequency Effect Between the Lexical Decision and Naming Tasks in Chinese

In psycholinguistic research, the frequency effect can be one of the indicators for eligible experimental tasks that examine the nature of lexical access. ...

The 4 Mountains Test: A Short Test of Spatial Memory with High Sensitivity for the Diagnosis of Pre-dementia Alzheimer's Disease

This protocol describes the administration of the 4 Mountains Test (4MT), a short test of spatial memory, in which memory for the topographical layout of ...

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task

This protocol describes a modified serial reaction time (SRT) task used to study implicit motor sequence learning. Unlike the classic SRT task that ...

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Investigating the interactions among multiple participants is a challenge for researchers from various disciplines, including the decision sciences and ...

The Unpredictable Chronic Mild Stress Protocol for Inducing Anhedonia in Mice

Depression is a highly prevalent and debilitating condition, only partially addressed by current pharmacotherapies. The lack of response to treatment by ...