NIAS CONSCIOUSNESS STUDIES PROGRAMME
Nithin Nagaraj

Person 3

Nithin Nagaraj is an Assistant Professor with the NIAS Consciousness Stdies Programme at the National Institute of Advanced Studies. He has Bachelors in Electrical and Electronics Engineering (1999) from National Institute of Technology Karnataka (formerly known as Karnataka Regional Engineering College, Surathkal), Masters in Electrical Engineering from Rensselaer Polytechnic Institute (RPI), Troy, New York (2001) and Ph.D. from National Institute of Advanced Studies (NIAS, 2010). His masters thesis at RPI was in the area of low complexity wavelet based moving color image coding. His doctoral dissertation at NIAS was in the area of ‘novel applications of chaos theory to coding and cryptography’.

He was a visiting faculty in Mathematics at IISER Pune for a semester before joining as Assistant Professor at the Department of Electronics and Communication Engineering, Amrita University for the period 2009-2013. At Amrita University, he taught several bachelors and masters level courses such as Signals and Systems, Digital Signal Processing, Information Theory and Coding, Cryptography, Wavelets and its Applications, Linear Algebra and Probability theory. He has also guided several Masters theses and Bachelor student projects in the areas of signal processing and communications. He has successfully guided 1 doctoral student from Amrita University in the field of complexity measures for time series analysis and classification. He also has several years of industry research experience. He worked as a Research Scientist (2001-2004) and Lead Scientist (2013-2015) at GE Global Research (Bengaluru) in the area of biomedical signal and image analysis. At GE Global Research, he has innovated on medical image compression algorithms, medical image segmentation and registration, lossless data embedding and ultrasound liver tissue characterization.

During his stint in the industry, he was a co-inventor of 8 U.S. patent applications (2 patents granted, all patents owned by GE). He joined the Consciousness Studies Programme at NIAS in October 2015. As a faculty of Consciousness Studies Programme, he has taught courses such as ‘Scientific Theories of Consciousness-I: Mathematical Methods’ and ‘Scientific Theories of Consciousness-II: Measures of Consciouness’. His current research interests include - Complexity Theories of Consciousness, Neural Signal Multiplexing, Causality Measures, Nonlinear Signal Processing and Chaos theory. He has published 14 international journal papers, over 40 national and international conference presentations with a total of 700+ citations and an h-index = 10 (source: Google Scholar). He has an Erdös Number of 3. He is an invited reviewer for the following international journals – Chaos (Amer. Inst. of Physics), European Physics Journal, Comm. in Non. Sci. Nonlinear Sim. (Elsevier), IEEE Transactions on Image Processing, Acta Applicandae Mathematicae, Intl. Journal of Imaging, EURASIP Journal of Information Security, Journal of Information Sciences (Elsevier), International Journal of Bifurcations and Chaos, IEEE Transactions on Information Forensics & Security, Computers and Mathematics with Applications (Elsevier), The Journal of Franklin Institute, Mathematical Problems in Engineering, Journal of Theoretical Biology.

His personal interests include popularizing mathematical thinking, study of Indian scriptures (Vedanta), and the practice of Atma Vichara.

Pic 01

The Neuroscience Approach to Understanding Consciousness

© Nithin Nagaraj

As you read these very words, you are receiving a rich variety of sensory signals – sound pressure at your eardrum, light intensity falling on your retina, sensations from the tip of your toe – all reaching your brain through voltage pulses called action potentials or ‘spikes’ transmitted via millions of sensory neurons. Brain, considered to be the seat of Mind & Consciousness, is in many ways the final frontier of scientific research. Theoretical or Computational Neuroscience aims to study how our brain encodes, performs computations on, and then decodes information from these ‘spikes’ in order to represent, interpret and understand the sensory world, and to initiate suitable actions (for eg., to move muscles in your eye to change the position of the eyeball) via information transmitted from the brain to the motor neurons.

The starting point of this study was the ground-breaking experiments of E. D. Adrian in the 1920s, who was the first to employ sensitive instruments to record from single axons of sensory receptor neurons (the first neurons he recorded were from stretch receptors in the muscle of the frog). These neurological signals, or ‘spike sequences’ are the language of the brain and nervous system, both for its internal communication and computation, and for external interaction with the outside world. The Central Questions Some of the central questions addressed by Neuroscience are – 1) How is information of the continuously varying external stimulus encoded (Neural Code) in to a ‘spike sequence’? 2) What is the information rate and coding efficiency of this Neural encoding? 3) How does the brain perform computation on these neurological signals? 4) Natural conditions impose a lot of noise on the ‘spike sequence’ – in such a scenario, how is encoding, processing and transmission performed with high reliability without error? 5) Given the sheer complexity of the number of neurons and their interconnections, how does such a highly complex, noisy network function 10 to yield (largely) consistent response and behavioural decisions from the organism? 6) How does memory play a role in all this? 9) Last and the most important – how does all this translate to the larger question of Mind and Consciousness?

The research teams in Neuroscience of today and tomorrow are made up of neurologists, electrical engineers and computer scientists, medical imaging researchers, physicists, psychiatrists, psychologists, neurosurgeons, mathematicians and philosophers (and not to forget animals and human volunteers for brain studies). Where Are We Today? Neuroscience has come a long way since the papyrus containing description of 48 cases related to the brain, written by an Egyptian surgeon thousands of years ago (an American Egyptologist named Edwin Smith first discovered this papyrus in 1862 AD). The Spanish Nobel laureate Santiago Cajal established the central tenet of modern neuroscience in 1889 – the ‘neuron doctrine’: that the nervous system is composed of discrete individual nerve cells which are independent elements (the term ‘neuron’ was coined by the German anatomist Wilhelm von Waldeyer in 1891 AD). Localism (the view that neurons and brain areas have specific functions) and holism (neurons work more as aggregate field) is now being replaced by “connectionism”. This view contends that lower level functions (primary sensory/motor functions) are strongly localized but higher-level functions (object recognition, memory, and language) are the result of interconnections 11 between different brain areas. In addition, even within areas that seem to be localized for a particular function, that function is found to be distributed among many neurons.

Pic 02

The Human Connectome project, sponsored by National Institute of Health (NIH, USA), by means of advanced high-field imaging technologies and neurocognitive tests attempts to construct a map of the complete structural and functional neural connections in vivo within and across individuals. This will produce a huge compilation of neural data from living human brains which will facilitate enhancing our understanding of the relationship between brain connectivity and behaviour, and also paving the way for research into brain disorders such as dyslexia, autism, Alzheimer’s disease, and schizophrenia. Brain-machine interfaces, high speed computing and virtual reality have enabled concrete scientific investigations into understanding how the brain creates a perception of reality and the mechanism of decision making in the brain. Brain-Computer and Brain-to-Brain interfaces have enabled unique insights in to the workings of the brain for understanding cognition and for restoring and augmenting brain function. Virtual reality based studies have addressed specifically how the brain creates perception of abstract space and time. Neuro-Imaging, Brain disorders and Consciousness Studies The advent of new functional neuro-imaging technologies such as Magnetoencephalography (MEG) which maps brain activity by recording magnetic fields produced by electrical currents occurring naturally in the brain, using highly sensitive magnetometers, and the classical functional- Magnetic Resonance Imaging (fMRI), not only are they useful for localizing regions in the brain which are pathological for surgical removal, these technologies are becoming increasingly useful for basic research into perceptual and cognitive brain processes, determining the function of various parts of the brain and for experimental neurofeedback.

Since its inception over twenty years ago, fMRI together with other measures of brain physiology (such as EEG) is increasingly being used for treating neurological disorders. These technologies enable to map functional areas of understanding and lateralization of language and memory in the brain, so 12 that surgeons can avoid removing critical brain regions whey they operate on brain tumours and lesions. However, there has been no progress in finding any region or structure of the brain that explains our own experience of a continuous, consistent, integrated and conscious “Self ”. Even to understand what determines subjective conscious experiences (qualia) has remained elusive to Neuroscience. End-Note Is the Mind completely “created” by the Brain? Can Consciousness be reduced to Neurons and their activities? Is there a “Soul or Self ” that exists beyond the Neurons? These questions continue to be hotly debated even today.

Publications

Nithin Nagaraj, Karthi Balasubramanian, "Dynamical Complexity Of Short and Noisy Time Series: Compression-Complexity vs. Shannon Entropy", European Physics Journal Special Topics (Special issue: Aspects of Statistical Mechanics and Dynamical Complexity), Jan. 2017, doi:10.1140/epjst/e2016-60397-x,

Karthi Balasubramanian, Nithin Nagaraj, "Aging and cardiovascular complexity: Effect of length of RR tachograms", PeerJ 4:e2755, Dec. 6 2016, https://doi.org/10.7717/peerj.2755.

Karthi Balasubramanian, Silpa S Nair, Nithin Nagaraj, "Classification of periodic, chaotic and random sequences using approximate entropy and Lempel-Ziv complexity measures", Pramana - Journal of Physics, Indian Academy of Sciences, Vol. 84, Issue 3, pp. 365 - 372, Feb. 2015.

Nithin Nagaraj, Karthi Balasubramanian, Sutirth Dey, "A New Complexity Measure For Time Series Analysis and Classification", Eur. Phys. J. Special Topics 222, pp. 847–860, 2013. (link) Download MATLAB code 'ETC.m'

Nithin Nagaraj, "One-Time Pad as a Nonlinear Dynamical System", Communications in Nonlinear Science and Numerical Simulation (Elsevier), Volume 17, Issue 11, pp. 4029–4036, Nov. 2012. doi: 10.1016/j.cnsns.2012.03.020

Nithin Nagaraj, "Huffman Coding as a Nonlinear Dynamical System", International Journal of Bifurcation and Chaos (IJBC), Volume: 21, Issue: 6, pp. 1727-1736, 2011. DOI No: 10.1142/S0218127411029392.

Sahasranand K. R., Nithin Nagaraj, Rajan S, "How Not to Share a Set of Secrets", International Journal of Computer Science and Information Security (IJCSIS), Vol. 8, No.1, pp. 234-237, Apr. 2010.