Emergence of functional neuroimaging, e.g. electroencephalogram (EEG), magnetoencephalogram (MEG) and functional magnetic resonance imaging (fMRI) has brought long-standing questions on human cognition under the purview of scientific exploration. However, none of these methods directly measure the neural activity of single brain cells. Hence, advanced quantitative tools are required to gain insights about underlying neural mechanisms. Furthermore, in real world cognition occurs in an interpersonal space involving multiple humans, which calls for understanding interactions between brains e.g., between speaker and listener. Our lab is devoted to the understanding of cognitive behaviour with a diverse set of tools ranging from building theoretical models of brain and behaviour, developing signal processing algorithms to study brain network mechanisms and studying cognitive phenomena through functional brain imaging techniques (EEG & MEG). Currently there are two main research directions in the lab.
Temporal microstructure of brain network mechanisms
Brain areas work harmoniously and engage in interactions with each other to facilitate ongoing behaviour. The nature of these interactions are constantly adapting to the demands of the environment. As an outcome no two instances of human performance are identical. For example, a batsman can have multiple ways to hit a cricket ball having an identical trajectory. Or, a classical musician often subtly adapts the same /raga to the acoustics of the environment. Hence, it is imperative to develop an understanding of human behaviour at the level of single trials. A long term goal of the lab is to develop signal processing tools to interpret the brain network mechanisms from EEG and MEG data which has high temporal resolution, in the order of milliseconds. These will be applied in understanding neurodynamics of decision making, multisensory processing and developing neuro-markers for brain disorders.
Temporal microstructure of brain network mechanisms
Brain areas work harmoniously and engage in interactions with each other to facilitate ongoing behaviour. The nature of these interactions are constantly adapting to the demands of the environment. As an outcome no two instances of human performance are identical. For example, a batsman can have multiple ways to hit a cricket ball having an identical trajectory. Or, a classical musician often subtly adapts the same /raga to the acoustics of the environment. Hence, it is imperative to develop an understanding of human behaviour at the level of single trials. A long term goal of the lab is to develop signal processing tools to interpret the brain network mechanisms from EEG and MEG data which has high temporal resolution, in the order of milliseconds. These will be applied in understanding neurodynamics of decision making, multisensory processing and developing neuro-markers for brain disorders.
Neural basis of speech processing and multisensory interactions
Speech is a fundamental medium of communication between human beings, well, at least till we learn to use Facebook. The seamless coordination between sensory systems that process what we hear, and what we see is an essential cog in learning how we speak. The role of vision is somewhat subtle and hence, unappreciated. Only under controlled settings do we realize how vision dramatically influences speech perception (see this YouTube link for demo, http://www.youtube.com/watch?v=aFPtc8BVdJk ). Our lab studies the neurobiological processes that facilitate creation, storage and finally, communication of speech sounds through a combination of approaches. From building theoretical models of speech perception to interpreting noninvasive brain scans on normal humans. Since, the purpose of speech is wireless communication between humans; we seek to study brain-to-brain interactions as a substrate of speech perception and production.