The universal grammar theory by Noam Chomsky, in linguistics, touches the very question of what defines us as uniquely human. Arguably, a philosophical view in pen and paper draft, it appeals to the dynamics of genotype information processing, in computer science, too.

My initial motivation to research on these topics begins with the graduate study at Caltech. I have been enrolled as a bachelor in information theory, but my scientific career has shifted there to computational physics and neuroscience. On a question about what he considers the most striking result in science, Richard Feynman's answer was that the stars are made of the same atoms as the earth. It reverberates in my memory even now. Communicating results in quantitative science have been made easier by the development of expressions in the language of mathematics.

In neuroscience, the advancement of mathematical tools to communicate data analysis has been slow due to the complexity of information to share. Nevertheless, the idea to conceptualize the knowledge within a unifying theory captures attention to many, notably amongst physicists.

I have been accepted in Professor Bela Julesz's Lab to work on mathematical modeling of his texton theory, in visual psychophysics. It was an inspiring time for me to work and learn from a great scientist, as well. I have published a paper on random stereograms1, but his ideas and devotion to scientific inquiry influenced my professional career, ever since.

I did my thesis work at the Belgrade University on learning and control of limb movements as a sequence of synergistic joint motions2. The equilibrium points hypothesis is generalized in memory, attention, and behavioral data study3. In our view, biological systems control movements at different levels of complexity via coordinate transformations, from accurately planned movements to reflexes.

At the Safarik University, we have studied a behavioral dimensionality paradigm along two dimensions, intensity and distance of an auditory signal4. We have shown a neuronal representation of sound distance in the human auditory cortex as a result of the information flow propagation in the brain. A distinct pattern of the scaling property of the information flow can be observed from the tonotopic map to the point of the intensity independent feature detector.

Computing and communication technology have grown exponentially in the second part of the last century. We have witnessed its ever increasing influence on our daily lives. At the dawn of the quantum computing era, it remains to be seen also how shall we conduct science to find solutions to the problems that have been shown intractable by the finite state's computers.

In particular, if machine learning and artificial intelligence would bring changes to knowledge discoveries. Or, if mathematics will remain a common language of expression like it has been since the time of Galileo and the beginning of the methodological approach to science.

"We can only see a short distance ahead, but we can see plenty there that needs to be done", seems appropriate words of a computing pioneer, Alan Turing.

References

1 Jovovic, M., A Markov random fields model for describing nonhomogeneous textures: generalized random stereograms, IEEE Workshop Proceedings on Visualization and Machine Vision, and IEEE Workshop Proceedings on Biomedical Image Analysis, Seattle 1994.
2 Jovovic, M., S. Jonic, D. Popovic, Automatic synthesis of synergies for control of reaching – hierarchical clustering. Medical Engineering and Physics 21/5:325-337, 1999.
3 Jovovic, M., Attention, Memories and Behavioral Data-driven Study, Advances in Neurology and Neuroscience, 2019.
4 Jovovic, M., Stochastic Resonance Synergetics – Quantum Information Theory for Multidimensional Scaling, Journal of Quantum Information Science, 5/2:47-57, 2015.