From Circuits to Consciousness
Welcome to my journey so far from the world of electronics and communication engineering to Consciousness research.
I began my career designing logic on circuit boards, only to realise the most complex operating system runs on wetware where there is no clear demarkation of the data, hardware and software. I traded silicon for synapses, and today, as a Cognitive Scientist at the Centre for Consciousness Studies (NIMHANS), my work revolves around multiple states of Consciousness across illness and wellness in wake, sleeping, meditating and dreaming brains.
I am establishing a research niche on “Sense of Self” exploring how it emerges, fragments, and can be altered in various states like Schizophrenia, Autism, Depression, Lucid dreaming, altered states in meditation etc. This work integrates neuroscience, psychiatry, technology, and contemplative science to understand the shifts of selfhood and their impact on mental health.
The Quiet Mind: Contemplative Science & Non-Linear Dynamics
During my MPhil research at NIMHANS and subsequent collaborations, I moved
beyond conventional EEG analysis to understand the “texture” of a meditating mind.
Standard EEG analysis often misses the nuance of multiple meditative states in
Vipassana meditation. I applied non-linear methods like Permutation Entropy and Fractal Dimension to high-density EEG data to capture these inherent structures.
More recently, we deployed ML based appraoches to understand how different meditation techniques lead to Similar States but Different Paths
The Sleeping Brain: Stability, Spindles, and Sound
My time as a Junior Research Fellow at the Human Sleep Research Laboratory was dedicated to understand the micro-architecture of sleep in Vipassana meditators and healthy controls. I conducted over 125 whole-night polysomnography (PSG) studies, using auditory stimulation and transcranial Alternating Current Stimulation (tACS) to “shake” the sleep architecture and test its stability. We identified that sleep ERPs and tACS-induced spectral changes could serve as reliable markers for sleep stability. More recently, I have prototyped MVPA pipelines to decode dream states from sleep data using machine learning classifiers.
I am currently exploring how microstate dynamics shift during sleep in both healthy brains and those affected by Schizophrenia. My work also includes developing machine learning classifiers to decode dream states from high-density PSG data using serial awakening protocols. I am also developing automated pipelines to capture sleep stage transitions and conceptualising sleep and awake across a continuum and deploying information theory and similar metrics to characterise sleep better.
Can we enhance our cognitive skills: Cognition & Neuromodulation
My PhD work focused on the “executive” of the brain: Working Memory. I wanted to know if we could map its limits and then push them using transcranial alternating current protocols. I designed a real-time adaptive working memory paradigm paired with high-density EEG to study the brain at its optimal capacity rather than at rest. Using tACS, I demonstrated that we could differentially modulate resting and task-related EEG data. By targeting specific frequencies (Theta and Gamma), we could influence the oscillatory dynamics underlying working memory. A significant portion of this work involved studying patients with Schizophrenia, using graph theory to identify specific profiles for targeted non-invasive neuromodulation.
The Cardiac Signature: Heart Rate Variability (HRV) & Heart-Brain Interaction
I am exploring Heart-Brain Connection using computational models of brain-heart interactions, and utilising robust and geometric versions of HRV analysis. We applied ultra short term heart rate variablity to understand OSA brains.
Teaching and Mentoring: Building the Lab
Science is rarely a solo endeavor. I have had the privilege of mentoring over 25 trainees and interns at NIMHANS, guiding them from modularised project ideas to full execution. Our collaborative projects have explored inter-brain synchrony during musical engagement , Heart Evoked Potentials across sleep stages, and the association between personality traits and executive control in school children. I collaborated with a bunch of hardware and software engineers to extend wireless wearable EEG devices with single-board computers for real-time neurofeedback and seizure prediction.