The Language Imaging Laboratory has developed and tested an extensive suite of computerized tests for assessing language deficits in people with aphasia. The battery focuses on lexical-level phonologic, orthographic, and semantic tasks that assess the hypothetical network shown in Figure 1. This schematic model illustrates minimal architectural elements needed to account for behaviors such as naming objects, comprehending speech, and reading. Evidence for the processing subcomponents of the model comes from decades of neuropsychological and psycholinguistic research documenting behavioral dissociations and effects of sublexical and lexical variables on processing speed (e.g., Caplan, 1992; Levelt, 1989; Nadeau et al., 2000; Shallice, 1989). We typically supplement the battery with standardized measures from the Alberta Language Function Assessment Battery (a computerized battery developed by Chris Westbury at the University of Alberta (www.psych.ualberta.ca/~westburylab/downloads/alfab.download.html)), with various standardized measures of executive function and processing speed, and with the short form of the Boston Diagnostic Aphasia Test to enable traditional syndromic classification.
Our aim in developing this battery was to create a set of well-controlled instruments for defining specific psycholinguistic processing deficits for use in voxel-based behavior-lesion mapping studies. Most of the tests are designed to manipulate multiple stimulus factors of potential interest (e.g., word frequency, imageability, length), and to provide reasonable statistical power for detecting sensitivity to these factors, thus the tests tend to be somewhat lengthy. Many of the tests began as materials for fMRI experiments (e.g., Binder et al., 1999; Binder et al., 2003; Binder et al., 2005a; Binder et al., 2006; Binder et al., 2005b; Desai et al., 2006; Liebenthal et al., 2005; Mano et al., 2013; Pillay et al., 2018; Sabsevitz et al., 2003). Meeting the rigorous methodological standards of these experiments required compilation of published databases and development of tools for computing n-gram and n-phone frequencies; orthographic and phonologic neighborhood density and neighbor frequencies; word frequencies; spelling-sound consistency metrics; and other variables relevant to word recognition and production. These tools, which include automated routines for generating novel pseudowords based on English serial letter dependencies, were made freely available to the research community in 2005 as “MCWord” and are available at www.neuro.mcw.edu/mcword. Orthographic and phonologic statistics are based on the English CELEX database (Baayen et al., 1995). Other data used for stimulus selection and matching include imageability ratings averaged from multiple sources (Bird et al., 2001; Clark & Paivio, 2004; Coltheart, 2003; Cortese & Fugett, 2004; Schock et al., 2012); familiarity and age-of-acquisition ratings (Bird et al., 2001; Coltheart, 2003; Gilhooly & Logie, 1980); and published picture recognition norms (Snodgrass & Vanderwart, 1980; Snodgrass & Yuditsky, 1996). Many of the tests have been normed using healthy control samples (n = 24-30, depending on test) that were age-, sex-, and education-matched to our typical stroke patient sample. Tests results can thus be transformed to z-scores as needed, although in typical applications the focus is on dissociations in performance within an individual and how these dissociations vary within the stroke patient sample. In this approach, patients provide their own internal control data (Binder et al., 2016; Pillay et al., 2017a; Pillay et al., 2018; Pillay et al., 2014b).
We test patients in a quiet clinic area within a closed room. Auditory and visual stimuli are presented using a computer to maximize standardization and efficiency of presentation. Manual responses are recorded using a touch-sensitive computer screen. Accuracy and response time are scored automatically for tests with manual choice responses. Spoken responses are automatically digitized into the computer (16 bit, 44.1 kHz) and later transcribed phonetically from the digital recordings. The apparatus (Figure 2) consists of a laptop computer running custom software programmed in the "LiveCode" environment (livecode.com), a touch-sensitive LCD screen (MicroTouch model KTLC-151OT), a headphone set worn by the examiner, and a headphone set with attached microphone (Audio-Technica ATH-PDG1) worn by the participant. The headset microphone ensures a constant mouth-microphone orientation and distance, crucial for obtaining high-SNR recordings.
Tests begin with a very simple instruction screen (typically a single sentence), which is read aloud to the participant, followed by a short set of practice trials in which the participant receives corrective feedback and further explanation as needed. All trials are initiated by the participant touching a green square on the screen, and participants are free to take breaks between trials and between tests as needed.
Errors on production tasks are categorized according to the following definitions:
|Semantic||semantically-related word||lamp » desk|
|Mixed||semantically- and phonemically-related word||shirt » skirt|
|Formal||phonemically-related word||lamp » damp|
|Regularization||phonetic pronunciation of an exception word||soot » /sut/|
|Formal Nonword||phonemically-related nonword||lamp » /bæmp/|
|Unrelated Word||unrelated word||bamp » mouse|
|Unrelated Nonword||unrelated nonword||lamp » /bos/|
|Omission||no complete response produced|
|Lexicalization||phonemically-related word||bamp » damp|
The following list contains links to pages describing the LIL tests in more detail.
Alexander, M. P., Friedman, R. B., Loverso, F., & Fischer, R. S. (1992). Lesion localization of phonological agraphia. Brain and Language, 43, 83-95.
Baayen, R. H., Piepenbrock, R., & Gulikers, L. (1995). The CELEX lexical database (CD-ROM) (2.5 ed.). Philadelphia: Linguistic Data Consortium, University of Pennsylvania.
Beauvois, M. F., & Derouesne, J. (1979). Phonological alexia: Three dissociations. Journal of Neurology, Neurosurgery, and Psychiatry, 42, 1115-1124.
Beauvois, M. F., & Dérouesné, J. (1981). Lexical or orthographic agraphia. Brain, 104, 21-49.
Binder, J. R., Frost, J. A., Hammeke, T. A., Bellgowan, P. S. F., Rao, S. M., & Cox, R. W. (1999). Conceptual processing during the conscious resting state: a functional MRI study. Journal of Cognitive Neuroscience, 11, 80-93.
Binder, J. R., McKiernan, K. A., Parsons, M., Westbury, C. F., Possing, E. T., Kaufman, J. N., et al. (2003). Neural correlates of lexical access during visual word recognition. Journal of Cognitive Neuroscience, 15, 372-393.
Binder, J. R., Medler, D. A., Desai, R., Conant, L. L., & Liebenthal, E. (2005a). Some neurophysiological constraints on models of word naming. Neuroimage, 27, 677-693.
Binder, J. R., Medler, D. A., Westbury, C. F., Liebenthal, E., & Buchanan, L. (2006). Tuning of the human left fusiform gyrus to sublexical orthographic structure. Neuroimage, 33, 739-748.
Binder, J. R., Pillay, S. B., Humphries, C. J., Gross, W. L., Graves, W. W., & Book, D. S. (2016). Surface errors without semantic impairment in acquired dyslexia: A voxel-based lesion-symptom mapping study. Brain, 139, 1517-1526.
Binder, J. R., Pillay, S. B., Humphries, C. J., Kraegel, P., & Book, D. S. (2017). Phoneme perception deficits from unilateral left hemisphere stroke: A voxel-based lesion correlation study. Paper presented at the Society for the Neurobiology of Language, Baltimore, MD, USA.
Binder, J. R., Westbury, C. F., Possing, E. T., McKiernan, K. A., & Medler, D. A. (2005b). Distinct brain systems for processing concrete and abstract concepts. Journal of Cognitive Neuroscience, 17, 905-917.
Bird, H., Franklin, S., & Howard, D. (2001). Age of acquisition and imageability ratings for a large set of words, including verbs and function words. Behavior Research Methods, Instruments, & Computers, 33, 73-79.
Bozeat, S., Lambon Ralph, M. A., Patterson, K., Garrard, P., & Hodges, J. R. (2000). Nonverbal semantic impairment in semantic dementia. Neuropsychologia, 38, 1207-1215.
Caplan, D. (1992). Language: structure, processing and disorders. Cambridge, MA: MIT Press.
Clark, J. M., & Paivio, A. (2004). Extensions of the Paivio, Yuille, and Madigan (1968) norms. Behavioral Research Methods, Instruments, & Computers, 36, 371-383.
Coltheart, M. (2003). MRC Psycholinguistic Database, from http://websites.psychology.uwa.edu.au/school/MRCDatabase/uwa_mrc.htm
Coltheart, M., Patterson, K., & Marshall, J. (1980). Deep dyslexia. London: Routledge & Kegan Paul.
Cortese, M. J., & Fugett, A. (2004). Imageability ratings for 3,000 monosyllabic words. Behavior Research Methods, Instruments, and Computers, 36, 384-387.
Damasio, H., Tranel, D., Grabowski, T., Adolphs, R., & Damasio, A. (2004). Neural systems behind word and concept retrieval. Cognition, 92, 179-229.
Dell, G. S., Schwartz, M. F., Martin, N., Saffran, E. M., & Gagnon, D. A. (1997). Lexical access in aphasic and nonaphasic speakers. Psychological Review, 104, 801-838.
Desai, R., Conant, L. L., Waldron, E., & Binder, J. R. (2006). FMRI of past tense processing: The effects of phonological complexity and task difficulty. Journal of Cognitive Neuroscience, 18, 278-297.
Forde, E. M. E., & Humphreys, G. W. (1999). Category-specific recognition impairments: a review of important case studies and influential theories. Aphasiology, 13, 169-193.
Gainotti, G. (2000). What the locus of brain lesion tells us about the nature of the cognitive defect underlying category-specific disorders: A review. Cortex, 36, 539-559.
Gilhooly, K. J., & Logie, R. H. (1980). Age of acquisition, imagery, concreteness, familiarity and ambiguity measures for 1944 words. Behaviour Research Methods and Instrumentation, 12, 395-427.
Goodglass, H., Hyde, M. R., & Blumstein, S. (1969). Frequency, picturability and availability of nouns in aphasia. Cortex, 5, 104-119.
Hammeke, T. A., Kortenkamp, S. J., & Binder, J. R. (2005). Normative data on 372 stimuli for descriptive naming. Epilepsy Research, 66, 45-57.
Howard, D., & Patterson, K. (1992). Pyramids and palm trees: A test of semantic access from pictures and words. London: Thames Valley Publishing.
Katz, R. B., & Goodglass, H. (1990). Deep dysphasia: Analysis of a rare form of repetition disorder. Brain and Language, 39, 153-185.
Kounios, J., & Holcomb, P. J. (1994). Concreteness effects in semantic processing: ERP evidence supporting dual-encoding theory. Journal of Experimental Psychology: Learning, Memory and Cognition, 20, 804-823.
Levelt, W. J. M. (1989). Speaking: From intention to articulation. Cambridge, MA: MIT Press.
Liebenthal, E., Binder, J. R., Spitzer, S. M., Possing, E. T., & Medler, D. A. (2005). Neural substrates of phonemic perception. Cerebral Cortex, 15, 1621-1631.
Mano, Q. R., Humphries, C. J., Desai, R., Seidenberg, M. S., Osmon, D. C., & Binder, J. R. (2013). The role of left occipitotemporal cortex in reading: Reconciling stimulus, task, and lexicality effects. Cerebral Cortex, 23, 988-1001.
Martin, N., Dell, G. S., Saffran, E. M., & Schwartz, M. F. (1994). Origins of paraphasias in deep dysphasia: Testing the consequences of a decay impairment to an interactive spreading activation model of lexical retrieval. Brain and Language, 47, 609-660.
Michel, F., & Andreewsky, E. (1983). Deep dysphasia: An analog of deep dyslexia in the auditory modality. Brain and Language, 18, 212-223.
Nadeau, S. E., Gonzalez Rothi, L. J., & Crosson, B. (2000). Aphasia and language: Theory to practice. New York: Guilford Press.
Paivio, A. (1971). Imagery and verbal processes. New York: Holt, Rinehart & Winston.
Patterson, K. E., Marshall, J. C., & Coltheart, M. (Eds.). (1985). Surface dyslexia: Neuropsychological and cognitive studies of phonological reading. Hillsdale, NJ: Lawrence Erlbaum Assoc.
Pillay, S. B., Binder, J. R., Humphries, C., Gross, W. L., & Book, D. S. (2017a). Lesion localization of speech comprehension deficits in chronic aphasia. Neurology, 88, 970-975.
Pillay, S. B., Gross, W. L., Graves, W. W., Humphries, C. J., Book, D. S., & Binder, J. R. (2018). The neural basis of successful word reading in aphasia. Journal of Cognitive Neuroscience, in press.
Pillay, S. B., Humphries, C. J., Stengel, B. C., Book, D. S., Gross, W. L., & Binder, J. R. (2014a). Category-related semantic impairment: A "chronometric" voxel-based lesion-symptom mapping study. Paper presented at the Society for the Neurobiology of Language, Amsterdam, Netherlands.
Pillay, S. B., Kraegel, P., Book, D. S., & Binder, J. R. (2017b). Lesion localization of a shared phonologic representation deficit on reading, rhyming, repetition, and short-term memory tasks. Paper presented at the Society for the Neurobiology of Language, Baltimore, MD, USA.
Pillay, S. B., Stengel, B. C., Humphries, C., Book, D. S., & Binder, J. R. (2014b). Cerebral localization of impaired phonological retrieval during rhyme judgment. Annals of Neurology, 76, 738-746.
Roeltgen, D. P., & Heilman, K. M. (1984). Lexical agraphia: Further support for the two-system hypothesis of linguistic agraphia. Brain, 107, 811-827.
Roeltgen, D. P., Sevush, S., & Heilman, K. M. (1983). Phonological agraphia: Writing by the lexical-semantic route. Neurology, 33, 755-765.
Sabsevitz, D. S., Medler, D. A., McKiernan, K. A., Seidenberg, M., & Binder, J. R. (2003). Distinct neural substrates for semantic processing of concrete and abstract nouns. Neuroimage, 19, S59.
Sabsevitz, D. S., Medler, D. A., Seidenberg, M., & Binder, J. R. (2005). Modulation of the semantic system by word imageability. Neuroimage, 27, 188-200.
Schock, J., Cortese, M. J., & Khanna, M. M. (2012). Imageability estimates for 3,000 disyllabic words. Behavioral Research Methods, 44, 374-379.
Shallice, T. (1989). From Neuropsychology to Mental Structure. Cambridge, UK: Cambridge University Press.
Snodgrass, J. G., & Vanderwart, M. (1980). A standardized set of 260 pictures: Norms for name agreement, image agreement, familiarity, and visual complexity. Journal of Experimental Psychology: Human Learning and Memory, 6, 174-215.
Snodgrass, J. G., & Yuditsky, T. (1996). Naming times for the Snodgrass and Vanderwart pictures. Behavior Research Methods, Instruments, & Computers, 28, 516-536.
Warrington, E. K., & Shallice, T. (1984). Category specific semantic impairments. Brain, 107, 829-854.
Westbury, C. (2007). ALFAB: The Alberta Language Function Assessment Battery (http://www.psych.ualberta.ca/~westburylab/downlaods/alfab.download.html)
Wise, R. J. S., Howard, D., Mummery, C. J., Fletcher, P., Leff, A., Büchel, C., et al. (2000). Noun imageability and the temporal lobes. Neuropsychologia, 38, 985-994.