Skip to main content
Log in

Tradeoffs of estimating reaction time with absolute and relative thresholds

  • Published:
Behavior Research Methods Aims and scope Submit manuscript

Abstract

Measuring the duration of cognitive processing with reaction time is fundamental to several subfields of psychology. Many methods exist for estimating movement initiation when measuring reaction time, but there is an incomplete understanding of their relative performance. The purpose of the present study was to identify and compare the tradeoffs of 19 estimates of movement initiation across two experiments. We focused our investigation on estimating movement initiation on each trial with filtered kinematic and kinetic data. Nine of the estimates involved absolute thresholds (e.g., acceleration 1000 back to 200 mm/s2, micro push-button switch), and the remaining ten estimates used relative thresholds (e.g., force extrapolation, 5% of maximum velocity). The criteria were the duration of reaction time, immunity to the movement amplitude, responsiveness to visual feedback during movement execution, reliability, and the number of manually corrected trials (efficacy). The three best overall estimates, in descending order, were yank extrapolation, force extrapolation, and acceleration 1000 to 200 mm/s2. The sensitive micro push-button switch, which was the simplest estimate, had a decent overall score, but it was a late estimate of movement initiation. The relative thresholds based on kinematics had the six worst overall scores. An issue with the relative kinematic thresholds was that they were biased by the movement amplitude. In summary, we recommend measuring reaction time on each trial with one of the three best overall estimates of movement initiation. Future research should continue to refine existing estimates while also exploring new ones.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data availability

The data and statistical analysis files for the present study are available at https://osf.io/RBYNF/. This experiment was not preregistered.

Code availability

G1.m is available for download from https://people.ok.ubc.ca/brioconn/gtheory/gtheory.html. There are also versions for SAS, SPSS, and R.

Notes

  1. The data and statistical analysis files for the present study are available at https://osf.io/RBYNF/.

  2. G1.m is available for download from https://people.ok.ubc.ca/brioconn/gtheory/gtheory.html. There are also versions for SAS, SPSS, and R.

References

  • Anson, J. G. (1989). Effects of moment of inertia on simple reaction time. Journal of Motor Behavior, 21(1), 60–71.

    Article  PubMed  Google Scholar 

  • Binsted, G., & Elliott, D. (1999). Ocular perturbations and retinal/extraretinal information: The coordination of saccadic and manual movements. Experimental Brain Research, 127(2), 193–206.

    Article  PubMed  Google Scholar 

  • Blinch, J., Kim, Y., & Chua, R. (2018). Trajectory analysis of discrete goal-directed pointing movements: How many trials are needed for reliable data? Behavior Research Methods, 50(5), 2162–2172.

    Article  PubMed  Google Scholar 

  • Blinch, J., Homes, J., Cameron, B. D., & Chua, R. (2021). Investigating information processing of the bimanual asymmetric cost with the response priming technique. Journal of Experimental Psychology: Human Perception and Performance, 47(5), 673–688.

    PubMed  Google Scholar 

  • Bonato, P., D’Alessio, T., & Knaflitz, M. (1998). A statistical method for the measurement of muscle activation intervals from surface myoelectric signal during gait. IEEE Transactions on Biomedical Engineering, 45(3), 287–299.

    Article  PubMed  Google Scholar 

  • Botwinick, J., & Thompson, L. W. (1966). Premotor and motor components of reaction time. Journal of Experimental Psychology, 71(1), 9.

    Article  PubMed  Google Scholar 

  • Brennan, R. L. (2001). Generalizability theory. Springer.

    Book  Google Scholar 

  • Brenner, E., & Smeets, J. B. J. (2019). How can you best measure reaction times? Journal of Motor Behavior, 51(5), 486–495.

    Article  PubMed  Google Scholar 

  • Brown, S. G., Roy, E. A., Rohr, L. E., & Bryden, P. J. (2006). Using hand performance measures to predict handedness. Laterality, 11(1), 1–14.

    Article  PubMed  Google Scholar 

  • Carson, R. G., Chua, R., Elliott, D., & Goodman, D. (1990). The contribution of vision to asymmetries in manual aiming. Neuropsychologia, 28(11), 1215–1220.

    Article  PubMed  Google Scholar 

  • Christina, R. W., & Rose, D. J. (1985). Premotor and motor reaction time as a function of response complexity. Research Quarterly for Exercise and Sport, 56(4), 306–315.

    Article  Google Scholar 

  • Chua, R., & Elliott, D. (1993). Visual regulation of manual aiming. Human Movement Science, 12(4), 365–401.

    Article  Google Scholar 

  • Corcos, D. M., Gottlieb, G. L., & Agarwal, G. C. (1988). Accuracy constraints upon rapid elbow movements. Journal of Motor Behavior, 20(3), 255–272.

    Article  PubMed  Google Scholar 

  • Cousineau, D. (2017). Varieties of confidence intervals. Advances in cognitive psychology, 13(2), 140–155.

    Article  PubMed  PubMed Central  Google Scholar 

  • Cronbach, L. J., Gleser, G. C., Nanda, H., & Rajaratnam, N. (1972). The dependability of behavioral measurements: Theory of generalizability of scores and profiles. Wiley.

    Google Scholar 

  • Darling, W. G., Cole, K. J., & Abbs, J. H. (1988). Kinematic variability of grasp movements as a function of practice and movement speed. Experimental Brain Research, 73(2), 225–235.

    Article  PubMed  Google Scholar 

  • Englund, M. P., & Patching, G. R. (2009). An inexpensive and accurate method of measuring the force of responses in reaction time research. Behavior Research Methods, 41(4), 1254–1261.

    Article  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.

    Article  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 

  • Fitts, P. M. (1954). The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental Psychology, 47(6), 381–391.

    Article  PubMed  Google Scholar 

  • Fitts, P. M., & Seeger, C. M. (1953). SR compatibility: spatial characteristics of stimulus and response codes. Journal of Experimental Psychology, 46(3), 199.

    Article  PubMed  Google Scholar 

  • Franks, I. M., Sanderson, D. J., & Van Donkelaar, P. (1990). A comparison of directly recorded and derived acceleration data in movement control research. Human Movement Science, 9(6), 573–582.

    Article  Google Scholar 

  • Gracco, V. L., & Abbs, J. H. (1986). Variant and invariant characteristics of speech movements. Experimental Brain Research, 65(1), 156–166.

    Article  PubMed  Google Scholar 

  • Hansen, S., Elliott, D., & Khan, M. A. (2007). Comparing derived and acquired acceleration profiles: 3-D optical electronic data analyses. Behavior Research Methods, 39(4), 748–754.

    Article  PubMed  Google Scholar 

  • Hansen, S., Glazebrook, C. M., Anson, J. G., Weeks, D. J., & Elliott, D. (2006). The influence of advance information about target location and visual feedback on movement planning and execution. Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale, 60(3), 200.

    Article  PubMed  Google Scholar 

  • Helmholtz, H. L. F. (1850). Über die Methoden, kleinste Zeittheile zu messen, und ihre Anwendung für physiologische Zwecke. Philos. Mag, 6, 313–325.

    Article  Google Scholar 

  • Henry, F. M., & Rogers, D. E. (1960). Increased response latency for complicated movements and a “memory drum” theory of neuromotor reaction. Research Quarterly, 31(3), 448–458.

    Google Scholar 

  • Hick, W. E. (1952). On the rate of gain of information. Quarterly Journal of Experimental Psychology, 4(1), 11–26.

    Article  Google Scholar 

  • Huynh, H., & Feldt, L. S. (1976). Estimation of the box correction for degrees of freedom from sample data in randomized block and split-plot designs. Journal of Educational Statistics, 1(1), 69–82.

  • Hyman, R. (1953). Stimulus information as a determinant of reaction time. Journal of Experimental Psychology, 45(3), 188–196.

    Article  PubMed  Google Scholar 

  • Kapoula, Z., & Robinson, D. A. (1986). Saccadic undershoot is not inevitable: Saccades can be accurate. Vision Research, 26(5), 735–743.

    Article  PubMed  Google Scholar 

  • Khan, M. A., Elliott, D., Coull, J., Chua, R., & Lyons, J. (2002). Optimal control strategies under different feedback schedules: Kinematic evidence. Journal of Motor Behavior, 34(1), 45–57.

    Article  PubMed  Google Scholar 

  • Klapp, S. T. (1995). Motor response programming during simple choice reaction time: The role of practice. Journal of Experimental Psychology: Human perception and performance, 21(5), 1015.

    Google Scholar 

  • Klapp, S. T. (2003). Reaction time analysis of two types of motor preparation for speech articulation: Action as a sequence of chunks. Journal of Motor Behavior, 35(2), 135–150.

    Article  PubMed  Google Scholar 

  • Klapp, S. T., & Maslovat, D. (2020). Programming of action timing cannot be completed until immediately prior to initiation of the response to be controlled. Psychonomic Bulletin & Review, 27(5), 821–832.

    Article  Google Scholar 

  • Krigolson, O., & Heath, M. (2004). Background visual cues and memory-guided reaching. Human Movement Science, 23(6), 861–877.

    Article  PubMed  Google Scholar 

  • Lacouture, Y., & Cousineau, D. (2008). How to use MATLAB to fit the ex-Gaussian and other probability functions to a distribution of response times. Tutorials in Quantitative Methods for Psychology, 4(1), 35–45.

    Article  Google Scholar 

  • Lacquaniti, F., & Soechting, J. F. (1982). Coordination of arm and wrist motion during a reaching task. Journal of Neuroscience, 2(4), 399–408.

    Article  PubMed  Google Scholar 

  • Lagasse, P. P., & Hayes, K. C. (1973). Premotor and motor reaction time as a function of movement extent. Journal of Motor Behavior, 5(1), 25–32.

    Article  PubMed  Google Scholar 

  • Lakens, D. (2013). Calculating and reporting the effect sizes to facilitate cumulative science: A practical primer for t-tests and ANOVAs. Frontiers in Psychology, 4, 863.

    Article  PubMed  PubMed Central  Google Scholar 

  • Lin, D. C., McGowan, C. P., Blum, K. P., & Ting, L. H. (2019). Yank: the time derivative of force is an important biomechanical variable in sensorimotor systems. Journal of Experimental Biology, 222(18), jeb180414.

    Article  PubMed  PubMed Central  Google Scholar 

  • Milner, A. D. (1986). Chronometric analysis in neuropsychology. Neuropsychologia, 24(1), 115–128.

    Article  PubMed  Google Scholar 

  • Mushquash, C., & O’Connor, B. P. (2006). SPSS and SAS programs for generalizability theory and analysis. Behavior Research Methods, 38(3), 542–547.

    Article  PubMed  Google Scholar 

  • Oldfield, R. C. (1971). The assessment and analysis of handedness: The Edinburgh inventory. Neuropsychologia, 9(1), 97–113.

    Article  PubMed  Google Scholar 

  • Oostwoud Wijdenes, L., Brenner, E., & Smeets, J. B. J. (2014). Analysis of methods to determine the latency of online movement adjustments. Behavior Research Methods, 46(1), 131–139.

    Article  PubMed  Google Scholar 

  • Posner, M. I. (2005). Timing the brain: Mental chronometry as a tool in neuroscience. PLoS Biology, 3(2), e51.

    Article  PubMed  PubMed Central  Google Scholar 

  • Rosenbaum, D. A. (1980). Human movement initiation: Specification of arm, direction, and extent. Journal of Experimental Psychology: General, 109(4), 444.

    Article  PubMed  Google Scholar 

  • Shepard, R. N., & Metzler, J. (1971). Mental rotation of three-dimensional objects. Science, 171(3972), 701–703.

    Article  PubMed  Google Scholar 

  • Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011). False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological Science, 22(11), 1359–1366.

    Article  PubMed  Google Scholar 

  • Simon, J. R. (1969). Reactions toward the source of stimulation. Journal of Experimental Psychology, 81(1), 174.

    Article  PubMed  Google Scholar 

  • Sternberg, S. (1966). High-speed scanning in human memory. Science, 153(3736), 652–654.

    Article  PubMed  Google Scholar 

  • Sternberg, S. (1969). The discovery of processing stages: Extensions of Donders’ method. Acta Psychologica, 30, 276–315.

    Article  Google Scholar 

  • Solnik, S., Rider, P., Steinweg, K., DeVita, P., & Hortobágyi, T. (2010). Teager-Kaiser energy operator signal conditioning improves EMG onset detection. European Journal of Applied Physiology, 110, 489–498.

    Article  PubMed  PubMed Central  Google Scholar 

  • Staude, G., Flachenecker, C., Daumer, M., & Wolf, W. (2001). Onset detection in surface electromyographic signals: A systematic comparison of methods. EURASIP Journal on Advances in Signal Processing, 2001(2), 1–15.

    Article  Google Scholar 

  • Stone, K. D., Bryant, D. C., & Gonzalez, C. L. R. (2013). Hand use for grasping in a bimanual task: Evidence for different roles? Experimental Brain Research, 224(3), 455–467.

    Article  PubMed  Google Scholar 

  • Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18(6), 643–662.

    Article  Google Scholar 

  • Teasdale, N., Bard, C., Fleury, M., Young, D. E., & Proteau, L. (1993). Determining movement onsets from temporal series. Journal of Motor Behavior, 25(2), 97–106.

    Article  PubMed  Google Scholar 

  • Telford, C. W. (1931). The refractory phase of voluntary and associative responses. Journal of Experimental Psychology, 14(1), 1–36.

    Article  Google Scholar 

  • Tomberg, C., Levarlet-Joye, H., & Desmedt, J. E. (1991). Reaction times recording methods: Reliability and EMG analysis of patterns of motor commands. Electroencephalography and Clinical Neurophysiology/Evoked Potentials Section, 81(4), 269–278.

    Article  Google Scholar 

  • Vannozzi, G., Conforto, S., & D’Alessio, T. (2010). Automatic detection of surface EMG activation timing using a wavelet transform based method. Journal of Electromyography and Kinesiology, 20(4), 767–772.

    Article  PubMed  Google Scholar 

  • Vispoel, W. P., Morris, C. A., & Kilinic, M. (2018). Applications of generalizability theory and their relations to classical test theory and structural equation modeling. Psychological Methods, 23(1), 1–26.

    Article  PubMed  Google Scholar 

  • Westwood, D., & Goodale, M. (2003). Perceptual illusion and the real-time control of action. Spatial Vision, 16(3), 243–254.

    Article  PubMed  Google Scholar 

  • Wundt, W. (1880). Grundzüge der physiologischen psychologie (2nd ed., 2 Vols.). Engelmann.

  • Zhang, X., & Zhou, P. (2012). Sample entropy analysis of surface EMG for improved muscle activity onset detection against spurious background spikes. Journal of Electromyography and Kinesiology, 22(6), 901–907.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

Our thanks to two anonymous reviewers for their insightful critiques.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jarrod Blinch.

Ethics declarations

Ethics approval

The Human Research Protection Program at Texas Tech University approved the study. The procedures used in this study adhere to the tenets of the Declaration of Helsinki.

Consent to participate

Informed consent was obtained from all individual participants included in the study.

Consent for publication

Not applicable.

Conflict of interest/Competing interests

The authors have no relevant financial or non-financial interests to disclose.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

Examples of the effective estimates of movement initiation

The figures below illustrate several estimates of movement initiation for one representative trial (participant 36, vision, block 1, trial 28). Each graph has three black vertical lines, which represent, in order, the go signal, movement initiation estimated by the switch, and movement termination.

Fig. 7
figure 7

Relative estimates of movement initiation based on 5% of maximum kinematics. Note. The grey dot shows the maximum of each kinematic, and the horizontal dashed line is 5% of that maximum. The vertical dashed line is when the kinematic data first exceeds the 5% thresholds.

Fig. 8
figure 8

Relative estimates of movement initiation based on the extrapolation of kinematics or kinetics. Note. The grey dots show 25% of maximum, 75% of maximum, and maximum kinematics or kinetics. The sloped dashed line goes from 75% to 25% and then extrapolates back to the baseline. The dashed horizontal line is the intersection of the sloped dashed line and baseline, which is the estimate of movement initiation.

Fig. 9
figure 9

Absolute estimates of movement initiation based on 50 mm/s and 1000 mm/s2. Note. The horizontal dashed line in the top and bottom graphs is 50 mm/s and 1000 mm/s2, respectively. The vertical dashed line is when the kinematic data first exceeds that threshold.

Fig. 10
figure 10

Absolute estimates of movement initiation based on 10 mm/s and 200 mm/s2. Note. The horizontal dashed line in the top and bottom graphs is 10 mm/s and 200 mm/s2, respectively. The vertical dashed line is when the kinematic data first exceeds that threshold.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Blinch, J., Trovinger, C., DeWinne, C.R. et al. Tradeoffs of estimating reaction time with absolute and relative thresholds. Behav Res (2023). https://doi.org/10.3758/s13428-023-02211-4

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.3758/s13428-023-02211-4

Keywords

Navigation