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Modality matters: Three auditory conflict tasks to measure individual differences in attention control

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Abstract

Early work on selective attention used auditory-based tasks, such as dichotic listening, to shed light on capacity limitations and individual differences in these limitations. Today, there is great interest in individual differences in attentional abilities, but the field has shifted towards visual-modality tasks. Furthermore, most conflict-based tests of attention control lack reliability due to low signal-to-noise ratios and the use of difference scores. Critically, it is unclear to what extent attention control generalizes across sensory modalities, and without reliable auditory-based tests, an answer to this question will remain elusive. To this end, we developed three auditory-based tests of attention control that use an adaptive response deadline (DL) to account for speed–accuracy trade-offs: Auditory Simon DL, Auditory Flanker DL, and Auditory Stroop DL. In a large sample (N = 316), we investigated the psychometric properties of the three auditory conflict tasks, tested whether attention control is better modeled as a unitary factor or modality-specific factors, and estimated the extent to which unique variance in modality-specific factors contributed incrementally to the prediction of dichotic listening and multitasking performance. Our analyses indicated that the auditory conflict tasks have strong psychometric properties and demonstrate convergent validity with visual tests of attention control. Auditory and visual attention control factors were highly correlated (r = .81)—even after controlling for perceptual processing speed (r = .75). Modality-specific attention control factors accounted for unique variance in modality-matched criterion measures, but the majority of the explained variance was modality-general. The results suggest an interplay between modality-general attention control and modality-specific processing.

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Notes

  1. Specific details regarding removed cases for the Auditory DL tasks are as follows: For Auditory Flanker DL, there was an initial sample of 312 subjects; 3 were identified as problematic, 3 were first-pass outliers, and 5 were second-pass outliers. For Auditory Simon DL, there was an initial sample of 314 subjects; 3 were identified as problematic, 5 were first-pass outliers, and 6 were second-pass outliers. For Auditory Stroop DL, there was an initial sample of 317 subjects; 0 were identified as problematic, 6 were first-pass outliers, and 1 was a second-pass outlier.

  2. For an in-depth analysis of selective visual arrays as a measure of attention control and working memory capacity, please see Martin et al. (2021).

  3. The tasks are available for download on the Open Science Framework, along with the raw data and R code used to score the data files and generate figures (https://osf.io/2zqe7/).

References

  • Anderson, J. R. (2005). Cognitive psychology and its implications. Macmillan.

    Google Scholar 

  • Baddeley, A. (1996). Exploring the central executive. The Quarterly Journal of Experimental Psychology Section A, 49(1), 5–28.

    Article  Google Scholar 

  • Burgoyne, A. P., & Engle, R. W. (2020). Attention control: A cornerstone of higher-order cognition. Current Directions in Psychological Science, 29(6), 624–630.

    Article  Google Scholar 

  • Burgoyne, A. P., Mashburn, C. A., Tsukahara, J. S., & Engle, R. W. (2022). Attention control and process overlap theory: Searching for cognitive processes underpinning the positive manifold. Intelligence, 91, 101629.

    Article  Google Scholar 

  • Burgoyne, A. P., Tsukahara, J. S., Mashburn, C. A., Pak, R., & Engle, R. W. (2023). Nature and measurement of attention control. Journal of Experimental Psychology: General, 152(8), 2369–2402. https://doi.org/10.1037/xge0001408

  • Chan, J. S., Merrifield, K., & Spence, C. (2005). Auditory spatial attention assessed in a flanker interference task. Acta acustica united with acustica, 91(3), 554–563.

    Google Scholar 

  • Cherry, E. C. (1953). Some experiments on the recognition of speech, with one and with two ears. The Journal of the Acoustical Society of America, 25(5), 975–979.

    Article  ADS  Google Scholar 

  • Christensen, T. A., Lockwood, J. L., Almryde, K. R., & Plante, E. (2011). Neural substrates of attentive listening assessed with a novel auditory Stroop task. Frontiers in Human Neuroscience, 4, 236.

    Article  PubMed  PubMed Central  Google Scholar 

  • Conners, C. K. (2014). Conners continuous auditory test of attention. (Conners CATA).

    Google Scholar 

  • Conway, A. R., Cowan, N., & Bunting, M. F. (2001). The cocktail party phenomenon revisited: The importance of working memory capacity. Psychonomic Bulletin & Review, 8, 331–335.

    Article  CAS  Google Scholar 

  • Corbetta, M. (1998). Frontoparietal cortical networks for directing attention and the eye to visual locations: Identical, independent, or overlapping neural systems? Proceedings of the National Academy of Sciences, 95(3), 831–838.

    Article  CAS  ADS  Google Scholar 

  • Cowan, N., Elliott, E. M., Scott Saults, J., Morey, C. C., Mattox, S., Hismjatullina, A., & Conway, A. R. (2005). On the capacity of attention: Its estimation and its role in working memory and cognitive aptitudes. Cognitive Psychology, 51, 42–100. https://doi.org/10.1016/j.cogpsych.2004.12.001

    Article  PubMed  PubMed Central  Google Scholar 

  • Dosenbach, N. U., Visscher, K. M., Palmer, E. D., Miezin, F. M., Wenger, K. K., Kang, H. C., et al. (2006). A core system for the implementation of task sets. Neuron, 50(5), 799–812.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Draheim, C., Harrison, T. L., Embretson, S. E., & Engle, R. W. (2018). What item response theory can tell us about the complex span tasks. Psychological Assessment, 30(1), 116.

    Article  PubMed  Google Scholar 

  • Draheim, C., Mashburn, C. A., Martin, J. D., & Engle, R. W. (2019). Reaction time in differential and developmental research: A review and commentary on the problems and alternatives. Psychological Bulletin, 145(5), 508.

    Article  PubMed  Google Scholar 

  • Draheim, C., Tsukahara, J. S., Martin, J. D., Mashburn, C. A., & Engle, R. W. (2021). A toolbox approach to improving the measurement of attention control. Journal of Experimental Psychology: General, 150(2), 242.

    Article  PubMed  Google Scholar 

  • Draheim, C., Tshukara, J. S., & Engle, R. W. (2023). Replication and extension of the toolbox approach to measuring attention control. Behavior Research Methods, 1–23.

  • Driver, J., & Frackowiak, R. S. (2001). Neurobiological measures of human selective attention. Neuropsychologia, 39(12), 1257–1262.

    Article  CAS  PubMed  Google Scholar 

  • Ekstrom, R. B., French, J. W., Harman, H. H., & Dermen, D. (1976). Manual for kit of factor-referenced cognitive tests: 1976. Educational Testing Service.

    Google Scholar 

  • Engle, R. W. (2002). Working memory capacity as executive attention. Current Directions in Psychological Science, 11(1), 19–23.

    Article  Google Scholar 

  • Engle, R. W. (2018). Working memory and executive attention: A revisit. Perspectives on Psychological Science, 13(2), 190–193.

    Article  MathSciNet  PubMed  Google Scholar 

  • Eriksen, B. A., & Eriksen, C. W. (1974). Effects of noise letters upon the identification of a target letter in a nonsearch task. Perception & Psychophysics, 16(1), 143–149. https://doi.org/10.3758/BF03203267

    Article  Google Scholar 

  • Fan, J. (2014). An information theory account of cognitive control. Frontiers in human neuroscience, 8, 680.

    Article  PubMed  PubMed Central  Google Scholar 

  • Fan, J., McCandliss, B. D., Sommer, T., Raz, A., & Posner, M. I. (2002). Testing the efficiency and independence of attentional networks. Journal of Cognitive Neuroscience, 14(3), 340–347.

    Article  PubMed  Google Scholar 

  • Farah, M. J., Wong, A. B., Monheit, M. A., & Morrow, L. A. (1989). Parietal lobe mechanisms of spatial attention: Modality-specific or supramodal? Neuropsychologia, 27(4), 461–470.

    Article  CAS  PubMed  Google Scholar 

  • Friedman, N. P., & Miyake, A. (2000). Differential roles for visuospatial and verbal working memory in situation model construction. Journal of Experimental Psychology: General, 129(1), 61.

    Article  CAS  PubMed  Google Scholar 

  • Gazzaley, A., & Nobre, A. C. (2012). Top-down modulation: Bridging selective attention and working memory. Trends in Cognitive Sciences, 16(2), 129–135.

    Article  PubMed  Google Scholar 

  • Green, J. J., Doesburg, S. M., Ward, L. M., & McDonald, J. J. (2011). Electrical neuroimaging of voluntary audiospatial attention: Evidence for a supramodal attention control network. Journal of neuroscience, 31(10), 3560–3564.

    Article  CAS  PubMed  Google Scholar 

  • Hallett, P. E. (1978). Primary and secondary saccades to goals defined by instructions. Vision Research, 18, 1279–1296.

    Article  CAS  PubMed  Google Scholar 

  • Hedge, C., Powell, G., & Sumner, P. (2018). The reliability paradox: Why robust cognitive tasks do not produce reliable individual differences. Behavior Research Methods, 50, 1166–1186.

    Article  PubMed  Google Scholar 

  • Heitz, R. P. (2014). The speed-accuracy tradeoff: History, physiology, methodology, and behavior. Frontiers in Neuroscience, 8, 150.

    Article  PubMed  PubMed Central  ADS  Google Scholar 

  • Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.

    Article  Google Scholar 

  • Hutchison, K. A. (2007). Attentional control and the relatedness proportion effect in semantic priming. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33(4), 645–662. https://doi.org/10.1037/0278-7393.33.4.645

    Article  PubMed  Google Scholar 

  • Ishigami, Y., Eskes, G. A., Tyndall, A. V., Longman, R. S., Drogos, L. L., & Poulin, M. J. (2016). The Attention Network Test-Interaction (ANT-I): Reliability and validity in healthy older adults. Experimental Brain Research, 234, 815–827.

    Article  PubMed  Google Scholar 

  • Jan, C., Li, S., Kang, M., Liu, L., He, L., Jin, L., Qin, X., Congdon, N., & Wang, K. (2019). Association of visual acuity with educational outcomes: A prospective cohort study. British Journal of Ophthalmology, 103(11), 1666–1671. https://doi.org/10.1136/bjophthalmol-2018-313294

    Article  PubMed  Google Scholar 

  • JASP Team (2023). JASP (Version 0.17.1) [Computer software].

  • James, W. (1890). The Principles of Psychology, I.

  • Kaernbach, C. (1991). Simple adaptive testing with the weighted up-down method. Perception & Psychophysics, 49(3), 227–229.

    Article  CAS  Google Scholar 

  • Kandel, E. R., Schwartz, J. H., & Jessell, T. M. (2000). Principles of neural science (4th ed.). McGraw-Hill.

    Google Scholar 

  • Kane, M. J., Bleckley, M. K., Conway, A. R., & Engle, R. W. (2001). A controlled-attention view of working-memory capacity. Journal of Experimental Psychology: General, 130(2), 169–183. https://doi.org/10.1037/0096-3445.130.2.169

    Article  CAS  PubMed  Google Scholar 

  • Kane, M. J., Hambrick, D. Z., Tuholski, S. W., Wilhelm, O., Payne, T. W., & Engle, R. W. (2004). The Generality of Working Memory Capacity: A Latent-Variable Approach to Verbal and Visuospatial Memory Span and Reasoning. Journal of Experimental Psychology: General, 133(2), 189–217. https://doi.org/10.1037/0096-3445.133.2.189

    Article  PubMed  Google Scholar 

  • Kerlin, J. R., Shahin, A. J., & Miller, L. M. (2010). Attentional gain control of ongoing cortical speech representations in a “cocktail party”. Journal of Neuroscience, 30(2), 620–628.

    Article  CAS  PubMed  Google Scholar 

  • Kline, R. B. (2023). Principles and practice of structural equation modeling. Guilford publications.

  • Lin, H. Y., Hsieh, H. C., Lee, P., Hong, F. Y., Chang, W. D., & Liu, K. C. (2017). Auditory and visual attention performance in children with ADHD: The attentional deficiency of ADHD is modality specific. Journal of Attention Disorders, 21(10), 856–864.

    Article  PubMed  Google Scholar 

  • Martin, J., Mashburn, C. A., & Engle, R. W. (2020). Improving the Validity of the Armed Service Vocational Aptitude Battery with Measures of Attention Control. Journal of Applied Research in Memory and Cognition, 9(3), 323–335.

    Article  Google Scholar 

  • Martin, J. D., Tsukahara, J. S., Draheim, C., Shipstead, Z., Mashburn, C. A., Vogel, E. K., & Engle, R. W. (2021). The visual arrays task: Visual storage capacity or attention control? Journal of Experimental Psychology: General, 150(12), 2525.

    Article  PubMed  Google Scholar 

  • Mashburn, C. A., Burgoyne, A. P., & Engle, R. W. (2023). Working memory, intelligence, and life success (p. 149). Memory in Science for Society.

    Google Scholar 

  • Mashburn, C. A., Burgoyne, A. P., & Engle, R. W. (under review). Knowledge, attention, and psychomotor ability: A latent variable approach to understanding individual differences in simulated work performance.

  • Miller, E. K., & Cohen, J. D. (2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24(1), 167–202.

    Article  CAS  PubMed  Google Scholar 

  • Nimon, K., Henson, R. K., & Gates, M. S. (2010). Revisiting interpretation of canonical correlation analysis: A tutorial and demonstration of canonical commonality analysis. Multivariate Behavioral Research, 45(4), 702–724.

    Article  PubMed  Google Scholar 

  • Overall, J. E., & Woodward, J. A. (1975). Unreliability of difference scores: A paradox for measurement of change. Psychological Bulletin, 82(1), 85.

    Article  Google Scholar 

  • Poghosyan, V., & Ioannides, A. A. (2008). Attention modulates earliest responses in the primary auditory and visual cortices. Neuron, 58(5), 802–813.

    Article  CAS  PubMed  Google Scholar 

  • Posner, M. I., & Driver, J. (1992). The neurobiology of selective attention. Current Opinion in Neurobiology, 2(2), 165–169.

    Article  CAS  PubMed  Google Scholar 

  • Psychology Software Tools, Inc. [E-Prime 3.0]. (2016). Retrieved from https://support.pstnet.com/

  • Purves, D., & Williams, S. M. (2001). Neuroscience (2nd ed.). Sinauer Associates.

    Google Scholar 

  • Raven, J. C., & Court, J. H. (1998). Raven's progressive matrices and vocabulary scales (Vol. 759). Oxford Psychologists Press.

    Google Scholar 

  • Redick, T. S., Heitz, R. P., & Engle, R. W. (2007). Working memory capacity and inhibition: Cognitive and social consequences. In D. S. Gorfein & C. M. MacLeod (Eds.), Inhibition in cognition (pp. 125–142). American Psychological Association. https://doi.org/10.1037/11587-007

    Chapter  Google Scholar 

  • Redick, T. S., Unsworth, N., Kelly, A. J., & Engle, R. W. (2012). Faster, smarter? Working memory capacity and perceptual speed in relation to fluid intelligence. Journal of Cognitive Psychology, 24(7), 844–854.

    Article  Google Scholar 

  • Rouder, J. N., & Haaf, J. M. (2019). A psychometrics of individual differences in experimental tasks. Psychonomic Bulletin & Review, 26(2), 452–467.

    Article  Google Scholar 

  • Rouder, J. N., Kumar, A., & Haaf, J. M. (2023). Why Many Studies of Individual Differences With Inhibition Tasks May Not Localize Correlation. PsyArXiV Preprint. https://doi.org/10.31234/osf.io/fsqvu

  • Salthouse, T. A., & Babcock, R. L. (1991). Decomposing adult age differences in working memory. Developmental Psychology, 27(5), 763.

    Article  Google Scholar 

  • Shah, P., & Miyake, A. (1996). The separability of working memory resources for spatial thinking and language processing: An individual differences approach. Journal of experimental psychology: General, 125(1), 4.

    Article  CAS  PubMed  Google Scholar 

  • Sheppard, L. D., & Vernon, P. A. (2008). Intelligence and speed of information-processing: A review of 50 years of research. Personality and individual differences, 44(3), 535–551.

    Article  Google Scholar 

  • Shipstead, Z., Lindsey, D. R., Marshall, R. L., & Engle, R. W. (2014). The mechanisms of working memory capacity: Primary memory, secondary memory, and attention control. Journal of Memory and Language, 72, 116–141. https://doi.org/10.1016/j.jml.2014.01.004

    Article  Google Scholar 

  • Simon, J. R., & Rudell, A. P. (1967). Auditory S-R compatibility: The effect of an irrelevant cue on information processing. Journal of Applied Psychology, 51(3), 300–304. https://doi.org/10.1037/h0020586

    Article  CAS  PubMed  Google Scholar 

  • Sohn, Y. W., & Doane, S. M. (2003). Roles of working memory capacity and long-term working memory skill in complex task performance. Memory & Cognition, 31, 458–466.

    Article  Google Scholar 

  • Spagna, A., Mackie, M. A., & Fan, J. (2015). Supramodal executive control of attention. Frontiers in Psychology, 6, 65.

    Article  PubMed  PubMed Central  Google Scholar 

  • Spearman, C. (1904). " General Intelligence," Objectively Determined and Measured. The American Journal of Psychology, 15(2), 201–292.

    Article  Google Scholar 

  • Sperry, R. W. (1993). The impact and promise of the cognitive revolution. American Psychologist, 48(8), 878.

    Article  Google Scholar 

  • Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18(6), 643–662. https://doi.org/10.1037/h0054651

    Article  Google Scholar 

  • Thurstone, L. L. (1938). Primary mental abilities. Psychometric Monographs.

    Google Scholar 

  • Treisman, A. (1964). Monitoring and storage of irrelevant messages in selective attention. Journal of Verbal Learning and Verbal Behavior, 3(6), 449–459.

    Article  Google Scholar 

  • Tsukahara, J. S., & Engle, R. W. under review. Sustaining the focus of attention and how it relates to performance in complex cognitive tasks. https://osf.io/wd5kz/download

  • Tsukahara, J. S., Harrison, T. L., Draheim, C., Martin, J. D., & Engle, R. W. (2020). Attention control: The missing link between sensory discrimination and intelligence. Attention, Perception, & Psychophysics, 82, 3445–3478.

    Article  Google Scholar 

  • Unsworth, N., Heitz, R. P., Schrock, J. C., & Engle, R. W. (2005). An automated version of the operation span task. Behavior Research Methods, 37(3), 498–505.

    Article  PubMed  Google Scholar 

  • Unsworth, N., Schrock, J. C., & Engle, R. W. (2004). Working memory capacity and the antisaccade task: Individual differences in voluntary saccade control. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30(6), 1302.

    PubMed  Google Scholar 

  • Vogel, E. K., McCollough, A. W., & Machizawa, M. G. (2005). Neural measures reveal individual differences in controlling access to working memory. Nature, 438(7067), 500–503.

    Article  CAS  PubMed  ADS  Google Scholar 

  • Walker, P. B., Olde, B. A., & Olson, T. M. (2007). Improving Aviator Selection Using the Performance-Based Measurement Battery (PBMB). Poster presented at the Proceedings of the Human Systems Integration Symposium. Annapolis Retrieved from https://www.researchgate.net/publication/266910869_Improving_Aviator_Selection_Using_the_Performance-Based_Measurement_Battery_PBMB

    Google Scholar 

  • Wang, L. J., Lee, S. Y., Tsai, C. S., Lee, M. J., Chou, M. C., Kuo, H. C., & Chou, W. J. (2021). Validity of visual and auditory attention tests for detecting ADHD. Journal of Attention Disorders, 25(8), 1160–1169.

    Article  PubMed  Google Scholar 

  • Wood, N. L., & Cowan, N. (1995). The cocktail party phenomenon revisited: Attention and memory in the classic selective listening procedure of Cherry (1953). Journal of Experimental Psychology: General, 124(3), 243.

    Article  CAS  PubMed  Google Scholar 

  • Wu, T., Chen, C., Spagna, A., Wu, X., Mackie, M. A., Russell-Giller, S., et al. (2020). The functional anatomy of cognitive control: A domain-general brain network for uncertainty processing. Journal of comparative neurology, 528(8), 1265–1292.

    Article  PubMed  Google Scholar 

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Author Note

Data, task downloads, and R code are openly available at https://osf.io/2zqe7/.

Funding

This work was supported by Office of Naval Research grants N00014-21-1-2327 and N00014-17-1-2061 and Naval Research Lab grants N00173-20-2-C003 and SA-GAT-NRL-0135-2019 to Randall W. Engle, and Office of Naval Research grant N00014-22-S-F002 to Randall W. Engle and Alexander P. Burgoyne.

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    Alexander P. Burgoyne, Dolly T. Seeburger & Randall W. Engle

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Appendix

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Fig. 19

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figure 19

Scree plot for exploratory factor analysis reported in Table 4

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Table 5 Performance on congruent and incongruent trials in the adaptive response deadline auditory conflict tasks
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Burgoyne, A.P., Seeburger, D.T. & Engle, R.W. Modality matters: Three auditory conflict tasks to measure individual differences in attention control. Behav Res (2024). https://doi.org/10.3758/s13428-023-02328-6

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