Faculty

Sridharan Devarajan

Associate Professor

Phone : +91 80 2293 3434
E-Mail : coglabcns.iisc[at]gmail.com
web : https.cns.iisc.ac.in/sridhar/

Research Areas

Cognition, Computation and Behaviour


Research Details

sridharan-1How does our brain enable us to pay attention selectively to some things, and to ignore others? What happens in the brain when we make important decisions? Our research focuses on understanding the neural basis of cognitive phenomena such as selective attention and decision making.

To address these questions we follow a quantitative approach that combines neuroscience experiments, model-based analyses (e.g., linear/nonlinear dynamical systems, control theory, machine learning) as well as large-scale computer simulations.

To develop and refine our hypotheses we directly measure or perturb brain activity in human subjects performing cognitively demanding tasks. We employ a variety of cutting-edge techniques, including functional neuroimaging (fMRI), diffusion imaging (dMRI), high-density electroencephalography (EEG), and transcranial electrical and magnetic stimulation (tES/tMS).

The overarching goal is to develop a unified framework that describes how cognitive phenomena emerge from neural computations by a systematic analysis of neurons and behavior. We are looking for students interested in understanding from diverse backgrounds (biology, computing, engineering, physics) to join us. For a flavor of some of our work (past and ongoing), do feel free to look around

Publications

Halder S., Raya D.V., Sridharan D., (2024), Distinct neural bases of subcomponents of the attentional blink, eLife

Chandrasekaran A. N., Vermani A., Gupta P., Steinmetz N., Moore T., Sridharan D., (2024), Dissociable components of attention exhibit distinct neuronal signatures in primate visual cortex, Science Advances, 10(5), 1-15 (Media coverage: Hindu | Times of India)

Gupta P., Sridharan D., (2024), Presaccadic attention does not facilitate the detection of changes in the visual field, PLOS Biology, 22(1), 1-28

Srivastava A., Shenoy p., Sridharan D., (2023), Avoiding catastrophic referral failures In medical images under domain shift, ICLR Workshop on Domain Generalization (Oral Presentation)

Link: https://cns.iisc.ac.in/sridhar/assets/publications/anuj_avoiding_catastrophic_referral.pdf

Umapathi B.M., Chauhan K., Shenoy P., Sridharan D., (2023), Shaken, and Stirred: Long-Range Dependencies Enable Robust Outlier Detection with PixelCNN++, International Joint Conference on Artificial Intelligence (IJCAI), 32, 1440-1450

Link: https://doi.org/10.24963/ijcai.2023/160

Sawant Y., Kundu J.N., Radhakrishnan V.B., Sridharan D., (2022), A Midbrain Inspired Recurrent Neural Network Model for Robust Change Detection, Journal of Neuroscience, 42 (44), 8262-8283

Link: https://doi.org/10.1523/JNEUROSCI.0164-22.2022

Chinchani A.M., Paliwal S., Ganesh S., Chandrasekhar V., Yu B.M., Sridharan D., (2022), Tracking momentary fluctuations in human attention with a cognitive brain-machine interface, Communications Biology, 5, 1346

Link: https://doi.org/10.1038/s42003-022-04231-w

Sreenivasan V., Kumar S., Pestilli F., Talukdar P., Sridharan D., (2022), GPU-accelerated connectome discovery at scale, Nature Computational Science, 2, 298-306

Link: https://doi.org/10.1038/s43588-022-00250-z

Chauhan K., Umapathi B.M., Shenoy P., Sridharan D., (2022), Robust outlier detection by de-biasing VAE likelihoods, Computer Vision and Pattern Recognition (CVPR), 9871-9880

Link: https://doi.ieeecomputersociety.org/10.1109/CVPR52688.2022.00965

Kushal Chauhan, Pradeep Shenoy, Manish Gupta, Devarajan Sridharan, (2021), Efficient remedies for outlier detection with variational autoencoders, Arxiv, (In submission)

Akshay Jagatap, Hritik Jain, Simran Purokayastha, Devarajan Sridharan, (2021), Neurally-constrained modeling of human gaze strategies in a change blindness task, PLoS Computational Biology, (In press)

Ajmera, S., Jain, H., Sundaresan, M. and Sridharan, D, (2020), Decoding task-specific cognitive states with slow, directed functional networks in the human brain, eNeuro, (in press)

*Ajmera, S., Rajagopal, S., Rehman, R. and Sridharan, D., (2019), Infra-slow brain dynamics as a marker for cognitive function and decline, Advances in Neural Information Processing Systems, (pp. 6947-6958)

*Sreenivasan, V. and Sridharan, D., (2019), Subcortical connectivity correlates selectively with attention’s effects on spatial choice bias, Proceedings of the National Academy of Sciences, 116(39), 19711-19716

Banerjee, S., Grover, S., Ganesh, S. and Sridharan, D*. , (2019), Sensory and decisional components of endogenous attention are dissociable, Journal of neurophysiology, 122(4), 1538-1554

Sagar, V., Sengupta, R., & Sridharan, D*., (2019), Exogenous attention facilitates performance through dissociable sensitivity and bias mechanisms, Scientific Reports, 9(1), 1-13

Kumar, S., Sreenivasan. V., Talukdar, P., Pestilli, F., Sridharan, D*., (2019), ReAl-LiFE: Accelerating the discovery of individualized brain connectomes on GPUs, In proceedings of the 33rd AAAI Conference on Artificial Intelligence, 33(1), , 630-638

Sagar, V., Sengupta, R., & Sridharan, D*., (2018), Exogenous attention facilitates performance through dissociable sensitivity and bias mechanisms, bioRxiv, 380659

Kundu, J. N., Srinivas, R., Babu, V. R., Sridharan, D*., (2017), A biologically-inspired sparse, topographic recurrent neural network model for robust change detection, NIPS workshop on Cognitively Informed Artificial Intelligence (CIAI), Oral spotlight presentation

Sundaresan, M., Nabeel, A., & Sridharan, D*., (2017), Mapping distinct timescales of functional interactions among brain networks, In Advances in Neural Information Processing Systems, (pp. 4109-4118)

Banerjee, S., Grover, S., Ganesh, S., & Sridharan, D*. , (2017), Sensory and decisional components of endogenous attention are dissociable, bioRxiv

Sridharan, D*., Steinmetz, N. A., Moore, T., & Knudsen, E. I., (2017), Does the superior colliculus control perceptual sensitivity or choice bias during attention? Evidence from a multialternative decision framework, Journal of Neuroscience, 37(3), 480-511

Knudsen, E. I., Schwarz, J. S., Knudsen, P. F., & Sridharan, D*. , (2017), Space-Specific Deficits in Visual Orientation Discrimination Caused by Lesions in the Midbrain Stimulus Selection Network, Current Biology, 27(14), 2053-2064

Banerjee, S., Grover, S., & Sridharan, D*., (2017), Unraveling Causal Mechanisms of Top-Down and Bottom-Up Visuospatial Attention with Non-invasive Brain Stimulation, Journal of the Indian Institute of Science, 97 (4), 451-475

Sridharan D*, Knudsen EI., (2015), Selective disinhibition: A unified neural mechanism for predictive and post hoc attentional selection, Vision Res, 116, 194-209.

Sridharan D*, Knudsen EI., (2015), Gamma oscillations in the midbrain spatial attention network: linking circuits to function, Curr Opin Neurobiol, 31, 189-198.

Sridharan D*, Ramamurthy DL, Schwarz JS, Knudsen EI., (2014), Visuospatial selective attention in chickens, Proceedings of the National Academy of Sciences, 111(19), E2056-E2065.

Sridharan D*, Schwarz JS, Knudsen EI., (2014), Selective attention in birds, Current Biology, 24(11), R510-513.

Sridharan D*, Steinmetz NA, Moore T, Knudsen EI., (2014), Distinguishing bias from sensitivity effects in multialternative detection tasks, Journal of Vision , 14(9), 16-16.

Sridharan D*, Ramamurthy DL, Knudsen EI., (2013), Spatial probability dynamically modulates visual target detection in chickens, Plos One, 8(5), e64136.

Schwarz JS, Sridharan D*, Knudsen EI., (2013), Magnetic tracking of eye position in freely behaving chickens, Frontiers in Systems Neuroscience , 7, 91.

Goddard CA, Sridharan D*, Huguenard JR, Knudsen EI, (2012), Gamma oscillations are generated locally in an attention-related midbrain network, Neuron, 73(3), 567-580

Sridharan D, Boahen K, Knudsen EI, (2011), Space coding by gamma oscillations in the barn owl optic tectum, Journal of Neurophysiology, 105(5), 2005-2017.

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