Abstract
Active Perception perspectives claim that action is closely related to perception. An empirical approach that supports these theories is the minimalist, in which participants perform a task using an interface that provides minimal information. Their exploratory movements are crucial to generating a meaningful sequence of information. Previous studies analyzed sensorimotor trajectories describing qualitative strategies and linear quantification of participants’ movement performance, but that approach struggles to capture the behavior of non-stationary data. In the present study, we applied the recurrence plot (RP) and recurrence quantification analysis (RQA) to study the structure of sensorimotor trajectories developed by participants trying to discriminate between two invisible geometric shapes (Triangle or Rectangle). The exploratory movements were made using a computer mouse and sonification-mediated feedback was provided, which depended exclusively on whether the pointer was inside or outside the shape. We applied RP and RQA to the sensorimotor trajectories, with the aim of studying their fine structure characteristics, focusing on their repetitive patterns. Recurrence analysis proved to be useful for quantifying differences in dynamic behavior that emerge when participants explore invisible virtual geometric shapes. The differences obtained in RQA-based measures associated with the vertical structures allowed to postulate the existence of particular exploration strategies for each figure. It was also possible to determine that the complexity of the dynamics changed according to the shape. We discuss these results in light of antecedents in haptic and visual perceptual exploration.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Availability of data
The dataset generated and analyzed during the current study is openly available in Zenodo at https://doi.org/10.5281/zenodo.5525112.
References
Afsar O, Tirnakli U, Marwan N (2018) Recurrence Quantification Analysis at work: Quasi-periodicity based interpretation of gait force profiles for patients with Parkinson disease. Sci Rep 8:9102. https://doi.org/10.1038/s41598-018-27369-2
Almeida TP, Schlindwein FS, Salinet J, Li X, Chu GS, Tuan JH, Stafford PJ, Ng GA, Soriano DC (2018) Characterization of human persistent atrial fibrillation electrograms using recurrence quantification analysis. Chaos Interdiscip J Nonlinear Sci 28(8):085710. https://doi.org/10.1063/1.5024248
Amamou Y, Stewart J (2006) Analyse comparative de trajectoires d’explorations perceptives. RJC-IHM’06. Anglet, France
Amamou Y, Stewart J (2007) Modelling Enactive Interaction with a perceptual supplementation device. In: 4th International conference on Enactive Interfaces, 33–36. Grenoble, France
Anderson NC, Bischof WF, Laidlaw KE, Risko EF, Kingstone A (2013) Recurrence quantification analysis of eye movements. Behav Res Methods 45(3):842–856. https://doi.org/10.3758/s13428-012-0299-5
Auvray M, Philipona D, O’regan JK, Spence C (2007) The perception of space and form recognition in a simulated environment: the case of minimalist sensory-substitution devices. Perception 36(12):1736–1751
Bermejo F, Di Paolo EA, Hüg MX, Arias C (2015) Sensorimotor strategies for recognizing geometrical shapes: a comparative study with different sensory substitution devices. Front Psychol 6:679. https://doi.org/10.3389/fpsyg.2015.00679
Bermejo F, Di Paolo EA, Gilberto LG, Lunati V, Barrios MV (2020) Learning to find spatially reversed sounds. Sci Rep 10(1):1–14
Chemero, A. (2011). Radical embodied cognitive science. MIT press.
Coco MI, Dale R (2014) Cross-recurrence quantification analysis of categorical and continuous time series: an R package. Front Psychol 5:510. https://doi.org/10.3389/fpsyg.2014.00510
Deschamps L, Le Bihan G, Lenay C, Rovira K, Stewart J, & Aubert D (2012) Interpersonal recognition through mediated tactile interaction. In: 2012 IEEE Haptics Symposium (HAPTICS), 239–245
Di Paolo EA, Buhrmann T, Barandiaran XE (2017) Sensorimotor life: An enactive proposal. Oxford University Press, Cambridge
Eckmann J-P, Kamphorst SO, Ruelle D (1987) Recurrence plots of dynamical systems. Europhys Lett 4:973–977
Fraser AM, Swinney HL (1986) Independent coordinates for strange attractors from mutual information. Phys Rev A 33(2):1134. https://doi.org/10.1103/PhysRevA.33.1134
Fusaroli R, Tylén K (2016) Investigating conversational dynamics: Interactive alignment, Interpersonal synergy, and collective task performance. Cogn Sci 40:145–217. https://doi.org/10.1111/cogs.12251
Gapenne O (2010) Kinesthesia and the construction of perceptual objects. En Stewart, J., Gapenne, O. y Di Paolo, E. (eds), Enaction: a new paradigm for cognitive science, MIT Press, Cambridge
Hasson CJ, Van Emmerik RE, Caldwell GE, Haddad JM, Gagnon JL, Hamill J (2008) Influence of embedding parameters and noise in center of pressure recurrence quantification analysis. Gait Posture 27(3):416–422. https://doi.org/10.1016/j.gaitpost.2007.05.010
Josiński H, Michalczuk A, Świtoński A, Szczęsna A, Wojciechowski K (2016) Recurrence plots and recurrence quantification analysis of human motion data. In: AIP Conference Proceedings. 1738(1), 180014. AIP Publishing LLC.
Kennel MB, Brown R, Abarbanel HD (1992) Determining embedding dimension for phase-space reconstruction using a geometrical construction. Phys Rev A 45(6):3403. https://doi.org/10.1103/PhysRevA.45.3403
Knight AP, Kennedy DM, McComb SA (2016) Using recurrence analysis to examine group dynamics. Group Dyn Theory Res Pract 20(3):223
Lederman SJ, Klatzky RL (1987) Hand movements: a window into haptic object recognition. Cogn Psychol 19:342–368. https://doi.org/10.1016/0010-0285(87)90008-9
Lederman SJ, Browse RA, Klatzky RL (1988) Haptic processing of spatially distributed information. Percept Psychophys 44:222–232. https://doi.org/10.3758/BF03206291
Lenay C, Steiner P (2010) Beyond the internalism/externalism debate: the constitution of the space of perception. Conscious Cogn 19(4):938–952
Leonardi G (2018) A Method for the computation of entropy in the Recurrence Quantification Analysis of categorical time series. Physica A 512:824–836. https://doi.org/10.1016/j.physa.2018.08.058
Marwan N (2008) A historical review of recurrence plots. Eur Phys J Special Topics 164(1):3–12. https://doi.org/10.1140/epjst/e2008-00829-1
Marwan N, Romano MC, Thiel M, Kurths J (2007) Recurrence plots for the analysis of complex systems. Phys Rep 438(5–6):237–329. https://doi.org/10.1016/j.physrep.2006.11.001
Marwan N (accessed 2020–05–04). Cross Recurrence Plot Toolbox for MATLAB®, Ver. 5.22 (R32.6), http://tocsy.pik-potsdam.de/CRPtoolbox/.
Morana C, Ramdani S, Perrey S, Varray A (2009) Recurrence quantification analysis of surface electromyographic signal: sensitivity to potentiation and neuromuscular fatigue. J Neurosci Methods 177(1):73–79. https://doi.org/10.1016/j.jneumeth.2008.09.023
Noë A (2004) Action in perception. MIT Press, Cambridge
O’Regan JK, Noë A (2001) A sensorimotor account of vision and visual consciousness. Behav Brain Sci 24(5):939–973
Richardson MJ, Chemero A (2014) Complex dynamical systems and embodiment. The Routledge handbook of embodied cognition, 39–50
Riley MA, Balasubramaniam R, Turvey MT (1999) Recurrence quantification analysis of postural fluctuations. Gait Posture 9(1):65–78. https://doi.org/10.1016/S0966-6362(98)00044-7
Riley MA, Wagman JB, Santana MV, Carello C, Turvey MT (2002) Perceptual behavior: recurrence analysis of a haptic exploratory procedure. Perception 31(4):481–510
Riley MA, Van Orden GC (2005) Tutorials in contemporary nonlinear methods for the behavioral sciences. National Science Foundation.
Ross JM, Balasubramaniam R (2015) Auditory white noise reduces postural fluctuations even in the absence of vision. Exp Brain Res 233(8):2357–2363. https://doi.org/10.1007/s00221-015-4304-y
Rovira K, Gapenne O (2009) Tactile classification of traditional and computerized media in three adolescents who are blind. J vis Impair Blind 103(7):430–435
Stewart J, Gapenne O (2004) Reciprocal modelling of active perception of 2-D forms in a simple tactile-vision substitution system. Mind Mach 14(3):309–330
Takens F (1981). Detecting strange attractors in turbulence. In: Rand D, Young LS (eds), Dynamical systems and turbulence, Warwick 1980 (vol 898, 366–381). Lecture Notes in Mathematics, Springer, Berlin
Thiel M, Romano MC, Kurths J, Meucci R, Allaria E, Arecchi FT (2002) Influence of observational noise on the recurrence quantification analysis. Physica D 171(3):138–152
Treisman AM, Gelade G (1980) A feature-integration theory of attention. Cogn Psychol 12:97–136. https://doi.org/10.1016/0010-0285(80)90005-5
Wagman JB, Shockley K, Riley MA, Turvey MT (2001) Attunement, calibration, and exploration in fast haptic perceptual learning. J Mot Behav 33(4):323–327. https://doi.org/10.1080/00222890109601917
Wallot S (2017) Recurrence quantification analysis of processes and products of discourse: a tutorial in R. Discourse Process 54(5–6):382–405. https://doi.org/10.1080/0163853X.2017.1297921
Wallot S, Leonardi G (2018) Analyzing multivariate dynamics using cross-recurrence quantification analysis (CRQA), diagonal-cross-recurrence profiles (DCRP), and multidimensional recurrence quantification analysis (MDRQA)–a tutorial in R. Front Psychol 9:2232. https://doi.org/10.3389/fpsyg.2018.02232
Wallot S, Mønster D (2018) Calculation of average mutual information (AMI) and false-nearest neighbors (FNN) for the estimation of embedding parameters of multidimensional time series in Matlab. Front Psychol 9:1679. https://doi.org/10.3389/fpsyg.2018.01679
Wallot S, Lyby M, van Rooij MJD (2015) Recurrence Quantification Analysis as a general-purpose tool for bridging the gap between qualitative and quantitative analysis. Qualitat Psychol Nexus 13:69–87
Webber CL Jr, Zbilut JP (1994) Dynamical assessment of physiological systems and states using recurrence plot strategies. J Appl Physiol 76(2):965–973. https://doi.org/10.1152/jappl.1994.76.2.965
Webber Jr, CL, Zbilut JP (2005) Recurrence quantification analysis of nonlinear dynamical systems. In: Tutorials in contemporary nonlinear methods for the behavioral sciences (142–177), eds M. A. Riley and G. C. Van Orden (Alexandria, VA: NSF)
Webber CL Jr, Marwan N (2015) Recurrence quantification analysis. Springer, Theory and Best Practices
Wu DWL, Anderson NC, Bischof WF, Kingstone A (2014) Temporal dynamics of eye movements are related to differences in scene complexity and clutter. J vis 14(9):8–8. https://doi.org/10.1167/14.9.8
Zbilut JP, Webber Jr, CL (2006) Recurrence quantification analysis. In: Wiley Encyclopedia of Biomedical Engineering, M. Akay (ed). https://doi.org/10.1002/9780471740360.ebs1355
Zbilut JP, Webber CL Jr (1992) Embeddings and delays as derived from quantification of recurrence plots. Phys Lett A 171(3–4):199–203. https://doi.org/10.1016/0375-9601(92)90426-M
Ziat M, Gapenne O, Stewart J, Lenay C (2007) Haptic recognition of shapes at different scales: A comparison of two methods of interaction. Interact Comput 19(1):121–132. https://doi.org/10.1016/j.intcom.2006.07.004
Acknowledgments
We wish to thank Gustavo Belbruno for his technical contribution to the setup of the experiment. In addition, we are much indebted to Moreno I. Coco and the two reviewers for their valuable comments and suggestions.
Funding
The work was partially supported by the Agencia Nacional de Promoción de la Investigación, el Desarrollo Tecnológico y la Innovación, FONCYT, Argentina (Grant numbers PICT 2018–2260 and PICT 2018–4593); the Universidad Tecnológica Nacional, Argentina (Grant number PID 5373); and the Universidad Nacional de Córdoba, Argentina (Grant number PID 472/2018).
Author information
Authors and Affiliations
Contributions
Fabián C. Tommasini, Diego A. Evin, Fernando Bermejo, and Mercedes X. Hüg contributed equally to the elaboration of this manuscript. Conceptualization: Fabián C. Tommasini, Diego A. Evin, Fernando Bermejo, Mercedes X. Hüg; Methodology: Fabián C. Tommasini, Diego A. Evin, Fernando Bermejo, Mercedes X. Hüg; Resources: M. Virginia Barrios; Investigation: Fernando Bermejo, M. Virginia Barrios; Data curation: Fabián C. Tommasini, Diego A. Evin; Formal analysis: Fabián C. Tommasini, Diego A. Evin, Mercedes X. Hüg; Software: Fabián C. Tommasini, Diego A. Evin, Augusto Pampaluna; Visualization: Fabián C. Tommasini, Diego A. Evin, Augusto Pampaluna; Writing—original draft preparation: Fabián C. Tommasini, Diego A. Evin, Fernando Bermejo, Mercedes X. Hüg; Funding acquisition: Fabián C. Tommasini, Diego A. Evin, Fernando Bermejo, Mercedes X. Hüg.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Ethics approval
The study was carried out in accordance with the 1964 Helsinki Declaration guidelines and its later amendments and was approved by the Institutional Ethics Committee (CIEIS Hospital Nacional de Clínicas, Universidad Nacional de Córdoba).
Consent to participate
All participants provided written informed consent prior to the beginning of the experiment.
Consent for publication
All participants signed informed consent regarding publishing the results obtained and preserving their personal data.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Handling editor: Moreno I. Coco (University of East London) Reviewers: Murillo Pagnotta (Center for Research and Interdisciplinarity, Paris) and a second researcher who prefers to remain anonymous.
Supplementary Information
Rights and permissions
About this article
Cite this article
Tommasini, F.C., Evin, D.A., Bermejo, F. et al. Recurrence analysis of sensorimotor trajectories in a minimalist perceptual task using sonification. Cogn Process 23, 285–298 (2022). https://doi.org/10.1007/s10339-021-01068-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10339-021-01068-9