Supratim Ray

Assistant Professor & Wellcome Trust DBT Intermediate Fellow

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

Attentional mechanisms

Research Details

Our senses convey rich and detailed information about the external world, but we can selectively attend to some details while ignoring others. This capacity for selective attention is critical for survival and essential for complex tasks. Problems with controlling and directing attention, such as attention deficit hyperactivity disorder (ADHD), can impair the ability of individuals to function normally. Understanding the mechanisms of attention is therefore an issue of both basic and clinical interest. Attentional mechanisms have been studied at several different recording scales – from single neurons in monkeys to diffuse population measures such as electro- or magneto-encephalography (EEG/MEG) 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. In particular, we focus on particular oscillations in the brain, such as the alpha (~10 Hz) or gamma rhythms (30-80 Hz), which are modulated by the attentional load. This research has four segments. First, we study the relationship between brain rhythms recorded at different scales with the spiking activity of the neurons recorded from monkeys. Second, we study how attention modulates the activity of neurons as well as the brain rhythms. Third, we collaborate with neurosurgeons who record from human brains and make similar recordings in monkeys, and aim to bridge the human and monkey recordings. This has direct applications in the diagnosis of brain disorders and in brain-machine interfaces. Finally, we develop signal-processing tools to study brain signals, which are highly non-stationary and often require special analysis techniques.


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

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

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

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

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

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

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

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

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

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

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