Research

The lab works on diverse areas of basic and applied neuroscience hence the name Integrative Neuroscience and Technology lab. We'd like to understand how the brain is organized in terms of various brain structures and organization of networks (structure). Then we'd like to understand the function of various parts of the brain. Once we have understood this, we'd like to create applications which are useful for the world.

The lab uses various tools to understand the brain like psychophysics, cognitive testing, neuroimaging (sMRI/fMRI) and neurophysiology (EEG/MEG/iEEG). We also think that philosophy about science impacts theory which in turn determines the experimental setup we create, the experiments we do and what we can know about the brain, so we think deeply about philosophy, theory, and experimentation methods.

Some project in the group are as follows:

Precision imaging/Neuroanatomy: The research arm is dedicated to understanding the organization of the brain using precision imaging tools. When we collect a large amount of fMRI data within an individual, we get a robust estimate of the brain connectivity which usually corresponds to multi synaptic connections in the brain. So in this arm, we collect precision imaging data to determine how the brain is organized across various levels.
Cognition: Understanding how cognitive modalities like perception, attention, working memory, long term memory, episodic projection, social cognition, meditation and consciousness works and how is it organized across parts of the brain. We predominantly use fMRI and EEG to understand the localization and dynamics of these various modalities.
NeuroAI - Predictive modeling: The principles of neuroscience impacts AI models and AI methods allow us to find interesting patterns in neural data. A major chunk of the research in the lab is to fit AI models on to neural data to make predictions about task state and cognition.
NeuroAI - Neuroscience to AI: This new research arm will be focussed on creating new architectures based on neuroscience principles that can improve AI models.
Consciousness and Yogic Sciences: The lab is interested in understanding consciousness and how different yogic techniques help reach different states of consciousness. We also aim to understand how yogic methods can help improve mental and physical health.
Deep phenotyping enabled precision biomarkers: Once we have understood how the brain works in the laboratory setting, we would need to understand it in the real world. The lab is keen on starting a research program to collect cognitive data in the real world and determine low cost measures of tracking brain health and activity across large populations.
Methods development: Development of scientific methods improve how we do science. The lab has been involved in the development of newer analysis tools and techniques like Temporal Synchronization Analysis and Connectome Fingerprinting.