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«A Thesis Presented in Partial Fulfillment of the Requirements for the Degree Master of Science Approved April 2014 by the Graduate Supervisory ...»

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to images with greater articulation, and images with motion blur. The findings suggest that the implied motion stimulus is psychophysically related to information processing (longer reaction time), which is consistent with previous research (Fawcett, Hillebrand, & Singh, 2007).

Second, we examined the validity of the implied motion training. The findings indicated that stimuli were displayed correctly, and it had an impact on participants’ performance.

Third, we examined whether performance on the implied motion task parallels the linear pattern found in response to n real motion task. The findings indicated that psychophysical processing of implied motion is different from that for real motion discrimination tasks. That is, exposure to implied motion leads to attainment the saturation point (overtraining) much faster than expected. In this experiment, the point of saturation was reached after day 2 of training (≈1400 frames). In addition, more training was detrimental to performance on day 3 (≈2400 frames) and on day 4 (≈3200 frames).

Taken together, the findings show that perceptual learning of the implied motion task occurs quickly as indicated by short amount of training time (number of training days) required to achieve increased performance (brain plasticity/malleability) on the cognitive measure in this study (CFFT). That is, in the current study a limited number of days and training trials on the implied motion task were sufficient for enhancement in CFFT.

Previous studies using subliminal and supraliminal real motion required a greater number of days and training trials. Future research should explore possible reasons for this difference.

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and number of training days. The findings indicated that performance increased only on day 2 and day 3 for 1.90Y and 1.20Y luminance levels, respectively, providing more evidence for overtraining after day 2.

Five, we examined the relationship between implied motion training and changes in CFFT. In this study we found that implied motion training leads to faster plasticity in CFFT than reported in previous studies using real motion stimuli. This is an interesting finding that should be explored in future studies. The results also suggest that prolonged exposure to directional implied motion is related to higher-level processing. The increase in CFFT occurred over the four days of training despite the decrease in performance on the implied motion task. It is unclear, however, if the increase in CFFT happened during or after the point of saturation, given that CFFT levels were measured in pre- (prior to the start of training on day 1) and post-tests (after completion of training on day 4) only.

The findings in the current study are only generalizable to psychophysical experimentations. More specifically, the changes in performance and reaction time reveal changes in neural network functioning. Neuroimaging (fMRI) might reveal possible changes in neural network structure (increase in neural cell number and synaptic density).

In addition, this study looked at healthy participants enrolled in the cognitive rigor and challenges of university life, therefore, the results allow limited generalizability. Future studies should be conducted with participants from the general non-university-go population. Also, would the same findings be found for individuals with low visual acuity or low cognitive abilities?

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second day of implied motion training. Future studies may examine the exact point of saturation in regards to number of days and number of trials for implied motion to occur.

The same analysis could be done to determine the number of days and trials leading to brain plasticity for critical flicker fusion and other cognitive tasks. In future studies, we also would like to examine the possible interaction effect between point of saturation and increase in CFFT. This would consist of measuring CFFT after each day of implied motion training.

In conclusion, the current study results revealed some interesting finding regarding the relationship between implied motion training (a perceptual task) and changes (plasticity/malleability) on CFFT, a cognitive ability indicator.

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back of the brain) and within the calcarine sulcus. Previous research has indicated that V1 is sensitive to orientation, direction-selective information, and low contrast information (Fahle & Poggio 2002).

2 Observer are first presented with three vertical lines, then they are instructed to identify whether the central line of a bisection stimulus was offset either to the right or to the left (Tartaglia, Bamert, Mast, & Herzog (2009).

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Colby, C. L., Duhamel, J. R., & Goldberg, M. E. (1993). Ventral intraparietal area of the macaque: anatomic location and visual response properties. Journal of neurophysiology, 69, 902-902.

Crist, R. E., Kapadia, M. K., Westheimer, G., & Gilbert, C. D. (1997). Perceptual learning of spatial localization: specificity for orientation, position, and context.

Journal of neurophysiology, 78(6), 2889-2894.

Curran, S., & Wattis, J. (2000). Critical flicker fusion threshold: a potentially useful measure for the early detection of Alzheimer's disease. Human Psychopharmacology: Clinical and Experimental, 15(2), 103-112.

Fahle, M., & Poggio, T. (Eds.). (2002). Perceptual learning. MIT Press.

Fahle, M. (2005). Perceptual learning: specificity versus generalization. Current opinion in neurobiology, 15(2), 154-160.

Fawcett, I. P., Hillebrand, A., & Singh, K. D. (2007). The temporal sequence of evoked and induced cortical responses to implied motion processing in human motion area V5/MT+. European Journal of Neuroscience, 26(3), 775-783.

Groth, A. (2013). Neural plasticity in lower- and higher-level visual cortex processing. (Order No. 1536508, Arizona State University). ProQuest Dissertations and Theses, 34. Retrieved from http://login.ezproxy1.lib.asu.edu/login?url=http://search.proquest.com/docview/1 353660939?accountid=4485. (1353660939).

Halstead, W. C. (1947). Brain and intelligence; a quantitative study of the frontal lobes.

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Hindmarch, I. (1988). Information processing, critical flicker fusion threshold and benzodiazepines: results and speculations. In Benzodiazepine Receptor Ligands, Memory and Information Processing (pp. 79-89). Springer Berlin Heidelberg.

Holmes, K. J., & Wolff, P. (2010). Simulation from schematics: dorsal stream processing and the perception of implied motion. In Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 2704-2709).

Hosokawa, T., Mikami, K., & Saito, K. (1997). Basic study of the portable fatigue meter:

effects of illumination, distance from eyes and age. Ergonomics, 40(9), 887-894.

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Kourtzi, Z., & Kanwisher, N. (2000). Activation in human MT/MST by static images with implied motion. Journal of cognitive neuroscience, 12(1), 48-55.

Lorteije, J. A., Barraclough, N. E., Jellema, T., Raemaekers, M., Duijnhouwer, J., Xiao, D.,... & Van Wezel, R. J. (2011). Implied motion activation in cortical area MT can be explained by visual low-level features. Journal of cognitive neuroscience, 23(6), 1533-1548.

Lorteije, J. A., Kenemans, J. L., Jellema, T., Van Der Lubbe, R. H., De Heer, F., & Van Wezel, R. J. (2006). Delayed response to animate implied motion in human motion processing areas. Journal of Cognitive Neuroscience, 18(2), 158-168.

Milner, A. D. & Goodale, M. A. (2008). Two visual systems re-viewed.

Neuropsychologia, 46(3), 774; 774-785.

Merigan, W. H., Byrne, C. E., & Maunsell, J. H. (1991). Does primate motion perception depend on the magnocellular pathway? The Journal of neuroscience, 11(11), 3422-3429.

Nealey, T. A. & Maunsell, J. H. R. (1994). Magnocellular and parvocellular contributions to the responses of neurons in macaque striate cortex. The Journal of Neuroscience, 14(4), 2069.

Nanez Sr., J. E., Holloway, S. R., Donahoe, C., & Seitz, A. R. (2006). Flicker fusion as a correlate of word decoding ability. Journal of Vision (Charlottesville, VA.) 6(6), 998; 998-1006.

Osaka, N., Matsuyoshi, D., Ikeda, T., & Osaka, M. (2010). Implied motion because of instability in Hokusai Manga activates the human motion-sensitive extrastriate visual cortex: an fMRI study of the impact of visual art. NeuroReport, 21(4), 264Pavan, A., Cuturi, L. F., Maniglia, M., Casco, C., & Campana, G. (2011). Implied motion from static photographs influences the perceived position of stationary objects.

Vision Research, 51(1), 187-194.

Proverbio, A. M., Riva, F., & Zani, A. (2009). Observation of static pictures of dynamic actions enhances the activity of movement-related brain areas. PLoS One, 4(5), e5389.

Priebe, N. J., Churchland, M. M., & Lisberger, S. G. (2002). Constraints on the source of short-term motion adaptation in macaque area MT. I. The role of input and intrinsic mechanisms. Journal of Neurophysiology, 88(1), 354.

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Sandrt, M. (1963). Critical flicker frequency in multiple sclerosis. Perceptual and motor skills, 16(1), 103-108.

Saucer TS, Sweetbaum H (1958) Perception of the Shortest Noticebale Dark Time be Schizophrenics. Science, 127: 698–699.

Saygin, A. P., McCullough, S., Alac, M., & Emmorey, K. (2010). Modulation of BOLD response in motion-sensitive lateral temporal cortex by real and fictive motion sentences. Journal of cognitive neuroscience, 22(11), 2480-2490.

Schiller PH, Logothetis NK, Charles ER (1991) Parallel pathways in the visual system:

their role in perception at isoluminance. Neuropsychologia, 29: 433–441.

Seitz, A. R., Nanez Sr, J. E., Holloway, S. R., & Watanabe, T. (2006). Perceptual learning of motion leads to faster flicker perception. PLoS One, 1(1), e28.

Seitz AR, Watanabe T (2003) Psychophysics: Is subliminal learning really passive?

Nature 422: 36.

Seitz, A., & Watanabe, T. (2005). A unified model for perceptual learning.Trends in cognitive sciences, 9(7), 329-334.

Tartaglia, E. M., Bamert, L., Herzog, M. H., & Mast, F. W. (2012). Perceptual learning of motion discrimination by mental imagery. Journal of vision, 12(6), 14.

Tartaglia, E. M., Bamert, L., Mast, F. W., & Herzog, M. H. (2009). Human perceptual learning by mental imagery. Current Biology, 19(24), 2081-2085.

Urgesi, C., Moro, V., Candidi, M., & Aglioti, S. M. (2006). Mapping implied body actions in the human motor system. The Journal of Neuroscience, 26(30), 7942William R., Shadish, Cook, T. D., & Campbell, D. T. (2002). Experimental and quasiexperimental designs for generalized causal inference. Wadsworth Cengage learning.

Winawer, J., Huk, A. C., & Boroditsky, L. (2008). A motion aftereffect from still photographs depicting motion. Psychological Science, 19(3), 276-283.

Wooten, B. R., Hammond, B. R., Land, R. I., & Snodderly, D. M. (1999). A practical method for measuring macular pigment optical density. Investigative Ophthalmology & Visual Science, 40(11), 2481-2489.

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Participants Performance on Luminance Difficulty by Training Day Figure 9 Participants CFFT (Hz) change Day 1 (baseline) vs. Day (4)


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