EASI Tennis^®
Research

Purpose: EASI Tennis Research (ETR) is an independent, charitable, medical research organization. The charter of ETR is (1) the discovery of new theories of learning that can be applied to brain trauma rehabilitation and to develop new methods of physical rehabilitation based on these theories; and (2) to develop an encephalitis awareness program to educate emergency room personnel, 911 rescue workers, and local and state law enforcement officers to the signs of encephalitis so that patients suffering from this complex disease can receive proper and timely medical attention.

The failure to correctly diagnose encephalitis has resulted in countless cases of persons becoming permanently brain damaged that could have been avoided with a simple encephalitis awareness education program.

ETR will use a revolutionary approach to scientific discovery by studying the learning dynamics of athletes training to be sports professionals. Our initial sport has been selected to be tennis (see Why Tennis?)due to the success in rehabilitating Becky (see Becky's Story) from viral encephalitis. The complex learning and training process that is necessary to become a tennis professional parallels in numerous respects the same processes we see in a brain trauma patient trying to regain complex neuro muscular skills that were lost due to their disease or accident.

This website will present the questions that are developed from this research and will present papers that describe the results and hypotheses that are derived from this research. It will maintain current news about the research directions, distribution or funds, and the details of the research for those who are interested.

While there is some question about the reproducibility of results obtained from using tennis as a venue of research, it is still possible to develop hypothesis from this data and then construct a controlled experiment that can confirm the results under laboratory conditions.

Walter J. Freeman III, MD,Ph.D.
(2000) “Neurodynamics: An Exploration of Mesoscopic Brain Dynamics” Springer. 

[with Núñez, R., editors] (1999) “Reclaiming Cognition”  Imprint Academic 

(1999) “How Brains Make Up Their Minds” Weidenfeld & Nicolson

(1995) “Societies of Brains” Lawrence Erlbaum.

(1975) “Mass Action in the Nervous System” Academic Press 

(2001) The neurobiology of semantics: How can machines be designed to have meanings?  Chapter in: Kitamura T. (ed.) What Should be Computed to Understand and Model Brain Function.  Singapore: World Scientific Press. 

(2000) Brain Dynamics: Brain Chaos and Intentionality. Chapter 10b in: “Integrative Neuroscience.  Bringing Together Biological, Psychological and Clinical Models of the Human Brain” Gordon, E. (ed.) Sydney Australia: Harwood Academic Publ., pp.163-171.

(2000) Brains create macroscopic order from microscopic disorder by neurodynamics in perception.  Chapter 7 in: Århem P,Blomberg C, Liljenström H (eds.) Disorder versus Order in Brain Function.  Essays in Theoretical Neurobiology.  Singapore: World Scientific Publishing, pp. 205-219.

(2000) Emotion is essential to all intentional behaviors. Chapter 8 in: Lewis MD, Granic I (eds.). “Emotion, Development, and Self-Organization”. Cambridge U.K.: Cambridge University Press. pp. 209-235.

[with Ohl, F.W., and Scheich, H.] (2001) “Change in pattern of ongoing cortical activity with auditory category learning” Nature 412: 733-736.  

(2000) “Mesoscopic neurodynamics: From neuron to brain” Journal of Physiology (Paris) 94: 303-322. 
 Walter J. Freeman III, Ph.D. (Cont’d)
 
(2000) “Perception of time and causation through the kinesthesia of intentional action”  Cognitive Processing 1: 18-34. 
[and Barrie J.M.] (2000) “Analysis of spatial patterns of phase in neocortical gamma EEGs in rabbit” Journal of Neurophysiology 84: 1266-1278. 

Ellen Langer, PhD
The Power of Mindful Learning

Yan Yufik, PhD.
1. Yufik, Y.M. Sheridan, T.B. 2002. Swiss Army knife and Ockham’s razor: Modeling and facilitating operator’s comprehension in complex dynamic tasks. IEEE Trans. SMC, Part A: Systems and Humans, vol. 32, 2, pp. 185-199.

2. Yufik, Y. M. 2002. Neuropsychology of  Comprehension. In: Alkon, D.L., Yufik, Y.M. McBride, D. (Eds). Paradigms in Cognitive Modeling. Springer Scientific (In preparation).

3. Yufik, Y.M. 2002. How the mind works. Proc. IEEE World Congress on Computational Intelligence, Honolulu, Hawaii, pp. 2255-2259.

4. Yufik, Y.M. Georgopoulos, A.P. 2002. Understanding understanding. Proc. ONR Technology for Collaborative C2 Workshop, San Diego, CA.

5. Landry, S.J., Sheridan, T.B. Yufik, Y.M. 2001. A methodology for studying cognitive groupings in a target-tracking task. IEEE Trans. Intelligent Transportation Systems, Special Issue on Air Traffic Control, 92-101.

7. Yufik, Y.M. 1999. Complexity, Coherence, Comprehension. Presented at the MIT/Santa Fe Complexity in Engineering Workshop, MIT,  Cambridge, MA.

10. Yufik, Y.M. Malhotra, R.P. 1998. Virtual Associative Networks: A new paradigm for sensor fusion. IEEE International. Symp. On Intelligence and Systems, Rockville, MD.

11. Yufik, Y.M., Alkon, D. 1998. Modeling Adaptation and Information Fusion in the Human Nervous System. Report. Office of Naval  Research.  Arlington, VA.

12. Yufik, Y.M. 1998. Virtual Associative Networks: A Framework for Cognitive Modeling. In: Pribram, K.H. (Ed.). Brain and Values. Lawrence Erlbaum Associates. pp. 109-177.

16. Yufik, Y.M.  1996.  Memory, complexity, and  control in biological and artificial systems. Proc. Int. IEEE Conf. on Intelligent Systems, NIST, MD, 309-317.

17. Yufik, Y.M., Voloshin, M. 1996. Memory Integration in Complex Learning: A Novel Network Modeling Approach.  Abstracts, Society for Neuroscience.  Washington, D.C.

19. Yufik, Y.M. Sheridan, T.B. 1995. Assessment and Modeling of Cognitive Complexity. Presented at the Cognitive Modeling Symposium at the NASA Ames Research Center, Moffett Field, CA.

23. Vekker, L.,Allen, J.A, Yufik. Y.M 1993. Psychophysiology of Cognitive Complexity. Proc. 5th Int. Con. on Human-Computer Interaction, Orlando, Florida, 605-611.

24. Yufik, Y.M., Sheridan, T.B. 1993. Measuring cognitive complexity of human-machine interface. Proc. 5th Int. Con. on Human-Computer Interaction, Orlando, Florida, 587-592.

29. Yufik, Y.M. 1990. Application of cognitive modeling and knowledge measurement in diagnosis and training of complex skills. Human-Computer Interaction - INTERACT' 90, D. Diaper et al. (Eds.) Elsevier Science Publishers. North-Holland,pp. 887-892.

Ray Brown, PhD
[with Berezdivin, R, and Chua, L.] (2001). “Chaos and Complexity”, International Journal of Bifurcation and Chaos. 11(1).

(September 1999). “On the solution of nonlinear functional, finite difference, composition and iterated equations”, Fractals.

[and Chua, L.] (1999). “Clarifying Chaos III: Stochastic Processes”  International Journal of Bifurcation and Chaos 9(5).

[and Chua, L.] (1998). “Clarifying Chaos II: Bernoulli Chaos”  International Journal of Bifurcation and Chaos 8(2).

[and Chua, L.] (1997). “Chaos: Generating Complexity from Simplicity”  International Journal of Bifurcation and Chaos 7(11).

[and Chua, L.] (1996). “From Almost Periodic to Chaotic: The Fundamental Map” International Journal of Bifurcation and Chaos 6(6).

[and Chua, L.] (1993b). “Dynamical Synthesis of Poincare Maps,” International Journal of Bifurcation and Chaos 3(5).

[and Chua, L.] (1993a). “Dynamical Integration,” International Journal of Bifurcation and Chaos 3(1).
(1992). “Generalizations of the Chua Equations,” International Journal of Bifurcation and Chaos 2(4).