Computer Vision for Plant Phenomics and Smart Agriculture

Computer Vision for Plant Phenomics and Smart Agriculture

Start Date - End Date

Computer Vision for Plant Phenomics and Smart Agriculture


Investigating Inhibitory Control of Actions using TMS-EEG: A Potential Clinical Tool to Identify Neural Markers of Cognitive Deficits in Impulse Control Disorders

Investigating Inhibitory Control of Actions using TMS-EEG: A Potential Clinical Tool to Identify Neural Markers of Cognitive Deficits in Impulse Control Disorders

Start Date - End Date

Research Initiation Grant to setup a TMS-EEG modality to investigate inhibitory control of actions in humans. Inhibitory control is a cognitive function that helps us override unwanted actions, thoughts and emotions. TMS-EEG will provide a new window into the brain processes involved in such a form of control through simultaneous stimulation and brain activity measurements.


Multi-modal Learning for Genetic Characterization of Tumors

Multi-modal Learning for Genetic Characterization of Tumors

Start Date - End Date

Research initiation grant for creating the research facilities at the institute.


MRI Image Quality Enhancement

MRI Image Quality Enhancement

Start Date - End Date

Designing deep learning models that can remove noise and various artifacts from the MRI images captured through the MRI scanners developed by SAMEER, Mumbai.


Slot machines in our pockets: Elucidating the neural effects of smartphone overuse on reward anticipation and reward processing

Slot machines in our pockets: Elucidating the neural effects of smartphone overuse on reward anticipation and reward processing

Start Date - End Date

We study the impact of smartphone use on the brain, focusing on the relationship between smartphone use and gambling. Does smartphone addiction have any similarity with gambling addiction? Secondly we also explore the possibility of using smartphones to study cognition in a more naturalistic way compared to traditional lab experiments.


Development of an oscillator network model of the brain that will enable hypothesis-driven perturbation-response experiments for early detection of neurodegenerative disorders

Development of an oscillator network model of the brain that will enable hypothesis-driven perturbation-response experiments for early detection of neurodegenerative disorders

Start Date - End Date

We will develop a network model of the healthy and diseased human brain. This model will be used to simulate brain stimulation paradigms for early detection of neurodegenerative disorders. As internal connectivity of the brain changes, its response (in terms of EEG) to external stimuli (such as TMS) also changes. Can we detect changes in internal connectivity based on the observed changes in EEG? What is the best way to do that? We will answer these questions in this project.