Study of selective attention at multiple scales of neural integration

Research Group

Supratim Ray and Govindan Rangarajan

Center for Neuroscience, IISc and Department of Mathematics, IISc

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. 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. In particular, we focus on particular brain rhythms, such as the alpha (~10 Hz) or gamma rhythms (30-80 Hz), which are modulated by the attentional load.

Project 1 – Linking Monkey and Human data

Problem: What is the relationship between brain signals obtained using microelectrodes in monkeys to the signals obtained using macro-electrodes in humans (such as EEG)? This research has applications in brain-computer interfacing and neural prosthesis.

Methods: We will make hybrid grids with micro and well as macro-electrodes and implant them in monkeys, and collaborate with neurosurgeons to get similar data in humans (epileptic patients who have implants for epilepsy monitoring). We will compare power spectra, perform avalanche analysis (self organized criticality) and a variety of connectivity analyses to study the relationship between brain signals across scales.

Preferred background: Electrical engineering: signal processing, computer science, mathematics, neuroscience

Project 2 – Study of Feature Attention Problem: We can pay attention to a specific location in space, which is called spatial attention. However, we can also pay attention to a specific feature, irrespective of location. For example, while trying to find a silver coloured key, we are attending to a specific feature (silver colour). How this is accomplished is not well understood? Does the brain selectively increase the sensitivity of neurons that are tuned to the feature of interest (neurons that respond to silver colour?). How is the communication between different brain areas modulated by feature based attention?

Methods: We will train monkeys to do a feature attention task and implant multi-electrode arrays to study the response properties of neurons processing a particular feature, and how attention modulates their responses. We will use time-frequency analysis techniques to study how brain rhythms are modulated by feature attention.

Preferred background: Electrical engineering: signal processing and time-frequency analysis, mathematics: stochastic processes, neuroscience (neurophysiology)