Supratim Ray

Associate Professor

Office : Ground floor of PRL at Central Animal Facility
Phone : 080-22933437
E-Mail : sray[at]iisc.ac.in
web : www.cns.iisc.ac.in/~sray/

Research Areas

Mechanisms of attention and gamma oscillations; Modeling and Signal Processing; Brain-Computer Interfacing

Research Details

Our lab studies the neural basis of selective attention, with a focus on a brain rhythm called “gamma” (30-80 Hz), which is modulated by attentional load and is thought to be linked to high-level cognitive processes. Attentional mechanisms have been studied at several different recording scales – from single neurons in monkeys to diffuse population measures such as electro-encephalography (EEG) in humans. However, the relationship between signals recorded from such different scales is poorly understood. The long-term goal of this research is to elucidate the mechanisms of attention by linking the neural recordings obtained from these vastly different scales. This involves recording of electrical activity from the brains of both humans and non-human primates using a variety of techniques while they are engaged in certain cognitive tasks, development of advanced signal processing techniques to build the “links” across recording scales, and mathematical modeling of brain signals, including gamma oscillations, using dynamical system approach as well as detailed biophysical models. Establishment of this cross-species, cross-scale link between brain signals has far reaching applications, such as in Brain-computer Interfacing (BCI) and clinical diagnosis of brain disorders.


Salelkar S, Somasekhar GM, and Ray S, (2018), Distinct frequency bands in the local field potential are differently tuned to stimulus drift rate, Journal of Neurophysiology, Accepted

Shirhatti V and Ray S, (2018), Red hues induce unusually large gamma oscillations in the primate primary visual cortex, PNAS, 115(17), 4489-94

Dinavahi MVPS*, Shirhatti V*, Ravishankar P* and Ray S, (2018), Large visual stimuli induce two distinct gamma oscillations in primate visual cortex, Journal of Neuroscience, 38(11), 2730-44

Subhash Chandran KS, Seelamantula CS, and Ray S, (2018), Duration Analysis Using Matching Pursuit Algorithm Reveals Longer Bouts of Gamma Rhythm, Journal of Neurophysiology, 119(3), 808-821

Biswas A and Ray S, (2017), Control of alpha rhythm (8-13 Hz) using neurofeedback, Journal of the Indian Institute of Science, 97:4, 527-531

Subhash Chandran K S, Mishra A, Shirhatti V and Ray S., (2016), Comparison of Matching Pursuit algorithm with other signal processing techniques for computation of the time-frequency power spectrum of brain signals, Journal of Neuroscience, 36(12): 3399-3408

Shirhatti V, Borthakur A, and Ray S, (2016), Effect of Reference Scheme on Power and Phase of the Local Field Potential, Neural Computation, Vol 28, No. 5:882-913. doi:10.1162/NECO_a_00827

Dubey A and Ray S, (2016), Spatial Spread of local field potential is band-pass in the primate visual cortex, Journal of Neurophysiology, 116(4):1986-99

Ray S and Maunsell, JHR, (2015), Do gamma oscillations play a role in cerebral cortex?, Trends in Cognitive Sciences, Vol. 19(2): 78-85

Ray S, (2015), Challenges in the quantification and interpretation of spike-LFP relationships, Current Opinion in Neurobiology, 31: 111-118

Srinath R and Ray S., (2014), Effect of Amplitude Correlations on Coherence in the Local Field Potential, Journal of Neurophysiology, 112(4):741-51

Ray S, Ni AM and Maunsell JHR., (2013), Strength of Gamma Rhythm depends on Normalization, PLoS Biology, 11(2):e1001477

Ni AM, Ray S and Maunsell JHR, (2012), Tuned Normalization Explains the Size of Attention Modulations, Neuron, 73(4):803-813

Ray S and Maunsell JHR, (2011), Different origins of gamma rhythm and high-gamma activity in macaque visual cortex, PLoS Biology, 9(4):e1000610

Ray S and Maunsell JHR, (2011), Network rhythms influence the relationship between spike-triggered local field potential and functional connectivity, J Neurosci, 31(35):12674-82

Ray S and Maunsell JHR., (2010), Differences in gamma frequencies across visual cortex restrict their possible use in computation, Neuron, 67:885-896