Attention, Perception, & Psychophysics

, Volume 76, Issue 8, pp 2465–2476 | Cite as

Peripheral vision and perceptual asymmetries in young and older martial arts athletes and nonathletes

  • Mónica Muiños
  • Soledad BallesterosEmail author


The present study investigated peripheral vision (PV) and perceptual asymmetries in young and older martial arts athletes (judo and karate athletes) and compared their performance with that of young and older nonathletes. Stimuli were dots presented at three different eccentricities along the horizontal, oblique, and vertical diameters and three interstimulus intervals. Experiment 1 showed that although the two athlete groups were faster in almost all conditions, karate athletes performed significantly better than nonathlete participants when stimuli were presented in the peripheral visual field. Experiment 2 showed that older participants who had practiced a martial art at a competitive level when they were young were significantly faster than sedentary older adults of the same age. The practiced sport (judo or karate) did not affect performance differentially, suggesting that it is the practice of martial arts that is the crucial factor, rather than the type of martial art. Importantly, older athletes lose their PV advantage, as compared with young athletes. Finally, we found that physical activity (young and older athletes) and age (young and older adults) did not alter the visual asymmetries that vary as a function of spatial location; all participants were faster for stimuli presented along the horizontal than for those presented along the vertical meridian and for those presented at the lower rather than at the upper locations within the vertical meridian. These results indicate that the practice of these martial arts is an effective way of counteracting the processing speed decline of visual stimuli appearing at any visual location and speed.


Aging Horizontal–vertical anisotropy Karate athletes Judo athletes Martial arts Peripheral vision 



This research was supported by grants from the Spanish Government (PSI2010-21609-C2-01) and the Madrid Community (S2010/BMD-2349) to S.B. We would like to thank all the volunteers who participated in this study. We thank José Manuel Reales and Julia Mayas for their valuable comments.


  1. Abernethy, B., Neal, R. J., & Koning, P. (1994). Visual-perceptual and cognitive differences between expert, intermediate, and novice snooker players. Applied Cognitive Psychology, 8, 185–211.CrossRefGoogle Scholar
  2. Anderson, R. S., Zlatkova, M. B., & Demirel, S. (2002). What limits detection and resolution of short-wavelength sinusoidal gratings across the retina. Vision Research, 42, 981–990.PubMedCrossRefGoogle Scholar
  3. Ando, S., Kida, N., & Oda, S. (2001). Central and peripheral visual reaction time of soccer players and nonathletes. Perceptual and Motor Skills, 92, 786–794.PubMedCrossRefGoogle Scholar
  4. Ando, S., Kida, N., & Oda, S. (2004). Retention of practice effects on simple reaction time for peripheral and central visual fields. Perceptual and Motor Skills, 98, 897–900.PubMedCrossRefGoogle Scholar
  5. Ando, S., Kokubu, M., Kida, N., & Oda, S. (2002). Attention can be oriented to intermediate locations within the large area of the visual field. Perceptual and Motor Skills, 95, 806–812.PubMedCrossRefGoogle Scholar
  6. Ball, K., Beard, D., Roenker, R., Miller, D., & Griggs, D. (1988). Age and visual search: Expanding the useful field of view. Journal of the Optical Society of America, 5, 2210–2219.PubMedCrossRefGoogle Scholar
  7. Ball, K., Owsley, C., & Beard, B. (1990). Clinical visual perimetry underestimates peripheral field problems in older adults. Clinical Vision & Science, 5, 113–125.Google Scholar
  8. Ballesteros, S., & Reales, J. M. (2004). Intact haptic priming in normal aging and Alzheimer’s disease: Evidence for dissociable memory systems. Neuropsychologia, 42, 1063–1070.PubMedCrossRefGoogle Scholar
  9. Ballesteros, S., Bischof, G., Goh, J., & Park, D. (2013a). Neural correlates of conceptual object priming in young and older adults: An event-related functional magnetic resonance imaging study. Neurobiology of Aging, 34, 1254–1264.PubMedCentralPubMedCrossRefGoogle Scholar
  10. Ballesteros, S., Mayas, J., & Reales, J. M. (2013b). Cognitive function in normal aging and in older adults with mild cognitive impairment. Psicothema, 25, 18–24.PubMedGoogle Scholar
  11. Ballesteros, S., Mayas, J., & Reales, J. M. (2013c). Does a physically active lifestyle attenuate decline in all cognitive functions in old age? Current Aging Science, 6, 189–198.PubMedCrossRefGoogle Scholar
  12. Ballesteros, S., Reales, J. M., Mayas, J., & Heller, M. A. (2008). Selective attention modulates visual and haptic repetition priming: Effects in aging and Alzheimer’s disease. Experimental Brain Research, 189, 473–483.PubMedCrossRefGoogle Scholar
  13. Baltes, P. B., & Lindenberger, U. (1997). Emergence of a powerful connection between sensory and cognitive functions across the adult life span: A new window to the study of cognitive aging? Psychology and Aging, 12, 12–21.PubMedCrossRefGoogle Scholar
  14. Berkley, M. A., Kitterle, F., & Watkins, D. W. (1975). Grating visibility as a function of orientation and retinal eccentricity. Vision Research, 15, 239–244.PubMedCrossRefGoogle Scholar
  15. Beurskens, R., & Bock, O. (2012). Age-related decline of peripheral visual processing: The role of eye movements. Experimental Brain Research, 217, 117–124.PubMedCentralPubMedCrossRefGoogle Scholar
  16. Butler, K. M., Zacks, R. T., & Henderson, J. M. (1999). Suppression of reflexive saccades in younger and older adults: Age comparisons on an antisaccade task. Memory & Cognition, 27, 584–591.CrossRefGoogle Scholar
  17. Carrasco, M., & Chang, I. (1995). The interaction of objective and subjective organizations in a localization search task. Perception & Psychophysics, 57, 1134–1150.CrossRefGoogle Scholar
  18. Carrasco, M., Evert, D., Chang, I., & Katz, S. M. (1995). The eccentricity effect: Target eccentricity affects performance on conjunction searches. Perception & Psychophysics, 57, 1241–1261.CrossRefGoogle Scholar
  19. Carrasco, M., & Frieder, K. S. (1997). Cortical magnification neutralizes the eccentricity effect in visual search. Vision Research, 37, 63–82.PubMedCrossRefGoogle Scholar
  20. Carrasco, M., Talgar, C., & Cameron, E. L. (2001). Characterizing visual performance fields: Effects of transient cover attention, spatial frequency, eccentricity, task and set size. Spatial Vision, 15, 61–75.PubMedCrossRefGoogle Scholar
  21. Chodzko-Zajko, W. J. (1991). Physical fitness, cognitive performance and aging. Medicine and Science in Sports and Exercise, 23, 868–872.PubMedCrossRefGoogle Scholar
  22. Chodzko-Zajko, W. J., & Moore, K. A. (1994). Physical fitness and cognitive functions in aging. Exercise and Sport Sciences Reviews, 22, 195–220.PubMedCrossRefGoogle Scholar
  23. Chodzko-Zajko, W. J., Schuler, P., Solomon, J., Heini, B., & Ellis, N. R. (1992). The influence of physical fitness on automatic and effortful memory changes in aging. International Journal of Aging & Human Development, 35, 265–285.CrossRefGoogle Scholar
  24. Ciuffreda, K. J. (2011). Simple eye-hand reaction time in the retinal periphery can be reduced with training: A review. Eye & Contact Lens: Science & Clinical Practice, 37, 145–146.CrossRefGoogle Scholar
  25. Colcombe, S. J., Erickson, K. I., Scalf, P.E., Kim, J. S., Prakash, R., McAuley, E., …, & Kramer, A. F. (2006). Aerobic exercise training increases brain volume in aging humans. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 11, 1160-1170. Google Scholar
  26. Colcombe, S. J., Kramer, A. F., Erickson, K. I., & Scalf, P. (2006b). The implications of cortical recruitment and brain. NeuroImage, 32, 1891–1904.CrossRefGoogle Scholar
  27. Curcio, C. A., Sloan, K. R., Kalina, R. E., & Hendrickson, A. E. (1990). Human photoreceptor topography. Journal of Comparative Neurology, 300, 5–25.PubMedCrossRefGoogle Scholar
  28. Davis, H. P., Trussell, L. H., & Klebe, K. J. (2001). A ten-year longitudinal examination of repetition priming, incidental recall, free recall, and recognition in young and elderly. Psychology and Aging, 3, 358–366.Google Scholar
  29. Davare, M., Andres, M., Cosnard, G., Thonnard, J. L., & Olivier, O. (2006). Dissociating the role of ventral and dorsal premotor cortex in precision grasping. The Journal of Neuroscience, 26(8), 2260–2268.PubMedCrossRefGoogle Scholar
  30. Erickon, K. I., & Kramer, A. F. (2009). Aerobic exercise effects on cognitive and neural plasticity. British Journal of Sports Medicine, 43, 22–24.CrossRefGoogle Scholar
  31. Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). Mini-Mental state: A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198.PubMedCrossRefGoogle Scholar
  32. Goldthorpe, J. H., & Hope, K. (1974). The social grading of occupations. Oxford: Clarendon Press.Google Scholar
  33. Golla, H., Ignashchenkova, A., Haarmeier, T., & Their, P. (2004). Improvement of visual acuity by spatial cueing: A comparative study in human and non-human primates. Vision Reseach, 44, 1589–1600.CrossRefGoogle Scholar
  34. Hedden, T., & Gabrieli, J. D. (2004). Insights into the ageing mind: A view from cognitive neuroscience. Nature Reviews. Neuroscience, 5, 87–96.PubMedCrossRefGoogle Scholar
  35. Helsen, W. F., & Pauwels, J. M. (1993). The relationship between expertise and visual information processing in sport. In J. L. Starkes & F. Allard (Eds.), Cognitive issues in motor expertise (pp. 109–134). Amsterdam: North-Holland.CrossRefGoogle Scholar
  36. Hötting, K., & Röder, B. (2013). Beneficial effects of physical exercise on neuroplasticity and cognition. Neuroscience and Biobehavioral Reviews, 37, 2268–2295.CrossRefGoogle Scholar
  37. Itoh, N., & Fukuda, T. (2002). Comparative study of eye movements in extent of central and peripheral vision and use by young and elderly walkers. Perceptual & Motor Skills, 94, 1283–1291.CrossRefGoogle Scholar
  38. Kappel, G. (1991). Design and analysis: A Researcher’s handbook (3rd ed.). Englewood Cliffs, NJ: Prentice Hall.Google Scholar
  39. Kibele, A. (2006). Non-consciously controlled decision making for fast motor reactions in sports. A priming approach for motor responses to non-consciously perceived movement features. Psychology of Sport and Exercise, 7, 591–610.CrossRefGoogle Scholar
  40. Kline, G. M., Porcari, J. P., Hintermeister, R., Freedson, P. S., Ward, A., McCarron, R. E, …, & Rippe, J. M. (1987). Estimation of VO2 max from a one-mile track walk, gender, age and body weight. Medicine and Science in Sports and Exercise, 19, 253-259.Google Scholar
  41. Kokubu, M., Ando, S., Kida, N., & Oda, S. (2006). Interference effects between saccadic and key-press reaction times of volleyball players and nonathletes. Perceptual & Motor Skills, 103, 709–716.Google Scholar
  42. Kramer, A. F., Bherer, L., Colcombe, S. J., Dong, W., & Greenough, W. T. (2004). Environmental influences on cognitive and brain plasticity during aging. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 59, M940–M957.CrossRefGoogle Scholar
  43. Lozano, R., Boada, M., Caballero, J. C., Flórez, F., Garay-Lillo, J., & González, J. A. (1999). ABC de las demencias. Barcelona: Eds. Mayo, S.A.Google Scholar
  44. Martínez, J., Onis, M. C., Duenas, R., Albert, C., Aquado, C., & Luque, R. (2002). Versión española del cuestionario de Yesevage abreviado (GDS) para el despistaje de depresión en mayores de 65 años: Adaptación y validación. Medifam, 12, 26–40.Google Scholar
  45. Memmert, D., Simons, D. J., & Grimme, T. (2009). The relationship between visual attention and expertise in sports. Psychology of Sport and Exercise, 10, 146–151.CrossRefGoogle Scholar
  46. Montaser-Kouhsari, L., & Carrasco, M. (2009). Perceptual asymmetries are preserved in short-term memory tasks. Attention, Perception, & Psychophysics, 71, 1782–1792.CrossRefGoogle Scholar
  47. Mori, S., Ohtani, Y., & Imanaka, K. (2002). Reaction times and anticipatory skills of karate athletes. Human Movement Science, 21, 213–230.PubMedCrossRefGoogle Scholar
  48. Muiños, M., & Ballesteros, S. (2013). Visuospatial attention and motor skills in kung fu athletes. Perception, 42, 1043–1050.PubMedCrossRefGoogle Scholar
  49. Müller, S., & Abernethy, B. (2012). Expert anticipatory skill in striking sports: A review and a model. Research Quarterly for Exercise and Sport, 83, 175–187.PubMedGoogle Scholar
  50. Osorio, A., Fay, S., Pouthas, V., & Ballesteros, S. (2010). Ageing affects brain activity in highly educated older adults: An ERP study using a word-stem priming task. Cortex, 46, 522–534.PubMedCrossRefGoogle Scholar
  51. Owsley, C., McGwin, G., & Searcey, K. (2013). A population-based examination of the visual and ophthalmological characteristics of licensed drivers aged 70 and older. The Journals of Gerontology. Series A Biological Science and Medical Sciences, 68, 567–573.CrossRefGoogle Scholar
  52. Paquette, C., & Fung, J. (2011). Old age affects gaze and postural coordination. Gait and Posture, 33, 227–232.PubMedCrossRefGoogle Scholar
  53. Park, D. C., Lautenschlager, G., Hedden, T., Davidson, N. S., Smith, A. D., & Smith, P. K. (2002). Models of visuospatial and verbal memory across the adult life span. Psychology and Aging, 17, 299–320.PubMedCrossRefGoogle Scholar
  54. Park, D. C., Polk, T. A., Mikels, J. A., Taylor, S. F., & Marshuetz, C. (2001). Cerebral aging: Integration of brain and behavioral models of cognitive function. Dialogues in Clinical Neurocience, 3, 151–165.Google Scholar
  55. Park, D. C., & Reuter-Lorenz, P. A. (2009). The adaptive brain: Aging and neurocognitive scaffolding. Annual Review of Psychology, 60, 173–196.PubMedCentralPubMedCrossRefGoogle Scholar
  56. Perrin, P., Deviterne, D., Hugel, F., & Perrot, C. (2001). Judo, better than dance, develops sensorimotor adaptabilities involved in balance control. Gait & Posture, 15, 187–194.CrossRefGoogle Scholar
  57. Perry, R. H., & Cowey, A. (1985). The ganglion cell and cone distribution in the monkey’s retina: Implications for central magnification factors. Vision Research, 25, 1795–1810.PubMedCrossRefGoogle Scholar
  58. Reisberg, B., Ferris, S. H., De León, M. J., & Crook, T. (1988). Global Deterioration Scale (GDS). Psychopharmacology Bulletin, 24, 661–663.PubMedGoogle Scholar
  59. Rovamo, J., & Virsu, V. (1979). An estimation and application of the human cortical magnification factor. Experimental Brain Research, 37, 1–20.CrossRefGoogle Scholar
  60. Salthouse, T. A. (1996). The processing speed theory of adult age differences in cognition. Psychological Review, 103, 403–428.PubMedCrossRefGoogle Scholar
  61. Salthouse, T. A., & Ferrer-Caja, E. (2003). What needs to be explained to account for age-related effects on multiple cognitive variables? Psychology & Aging, 18, 91–110.CrossRefGoogle Scholar
  62. Sánchez-López, J., Fernández, T., Silva-Pereyra, J., & Martínez, J. A. (2013). Differences between judo, taekwondo and kung-fu athletes in sustained attention and impulse control. Scientific Research, 4, 607–612.Google Scholar
  63. Sebastián, M., & Ballesteros, S. (2012). Effects of normal aging on event-related potentials and oscillatory brain activity during a haptic repetition priming task. NeuroImage. 60, 7–20.Google Scholar
  64. Schneider, W., Eschman, A., & Zuccolotto, A. (2002). E-prime user’s guide. Pittsburgh: Psychology Software Tools Inc.Google Scholar
  65. Sterkowicz, S., Lech, G., Jaworski, J., & Ambrozy, T. (2012). Coordination motor abilities of judo contestants at different age. Journal of Combat Sports and Martial Arts, 1, 5–10.CrossRefGoogle Scholar
  66. Voelcker-Rehage, C., & Niemann, C. (2013). Structural and functional brain changes relate to different types of physical activity across the life span. Neuroscience and Biobehavioral Reviews, 37, 2268–2295.PubMedCrossRefGoogle Scholar
  67. Wahl, H. W., Schmitt, M., Danner, D., & Coppin, A. (2010). Is the emergence of functional ability decline in early old age related to change in speed of cognitive processing and also to change in personality? Journal Aging Health, 22, 691–712.CrossRefGoogle Scholar
  68. Williams, A. M., Davids, K., Burwitz, L., & Williams, J. C. (1994). Visual search strategies in experienced and inexperienced soccer players. Research Quarterly for Exercise and Sport, 65, 127–135.PubMedCrossRefGoogle Scholar
  69. Wu, Y., Zeng, Y., Zhang, L., Wang, S., Wang, D., Tan, X., …, & Zhang, J. (2013). The role of visual perception in action anticipation in basketball athletes. Neuroscience, 237, 29–41.Google Scholar
  70. Zwierko, T. (2007). Differences in peripheral perception between athletes and nonathletes. Journal of Human Kinetics, 19, 53–62.Google Scholar
  71. Zwierko, T., Osinki, W., Lubinski, W., Czepita, D., & Florkiewicz, B. (2010). Speed of visual sensorimotor processes and conductivity of visual pathway in volleyball players. Journal of Human Kinetics, 23, 21–27.CrossRefGoogle Scholar

Copyright information

© The Psychonomic Society, Inc. 2014

Authors and Affiliations

  1. 1.Universitat Jaume ICastellónSpain
  2. 2.Studies on Aging and Neurodegenerative Diseases Research Group, Department of Basic Psychology IIUniversidad Nacional de Educación a DistanciaMadridSpain

Personalised recommendations