For decades, the field of neuroscience has greatly benefited from conducting experiments in meticulously controlled environments. This is because the brain's interaction with the outside world is highly complex and the effect of one environmental variability is likely to be confounded by many others. Therefore, classically, neuroscientists probe the brain in repeated and carefully timed conditions, allowing a few variables at a time. Increasing the number of variables, one needs an exponentially higher amount of data to maintain the statistical power, a concept known as the curse of dimensionality. With recent advances in data-driven modeling and high-throughput computing, processing large amount of high-dimensional data in a reasonable time is feasible. Additionally, recording many channels of brain and body activity allows us to study neural correlates of ecologically valid behavior. As the animals' decision process continuously unfolds, we aim to understand the aspects of the decision-making taking place, such as when to decide, where is the animal, and which option was chosen. We identify computational components in cortical areas that are representing this process within the high-dimensional space of the activities of anatomical units, a.k.a. spiking neurons. Findings from this research will bring us closer to understanding successes and failures of decision making in real-life scenarios.

Surviving in the wild requires that primates stay aware of their surrounding while focusing on goal-directed activities. We aim to identify the state of vigilance, defined as the degree to which an individual seeks information from their surroundings, in macaques and humans by monitoring their bodily and eye movements in controlled naturalistic environments. In macaques, we investigate how the natural states of vigilance are represented in frontal and parietal cortical circuits and influence foraging behavior. We employ a range of computational techniques to understand the richness and complexity of human and macaque behavior in similar scenarios while employing high-throughput electrophysiology to investigate the high-dimensional cortical activity. Findings from this project will help explain the representation of the inner state of vigilance in overt behavior and cortical activity and its potential influence on natural variability in goal-directed behavior.

Complex decision-making requires orchestrated activity across many brain areas that are representing external or internal information. Using state-of-the-art electrophysiological devices, we simultaneously probe multiple brain areas, each at many sites. We identify precisely timed coordinated activity across recorded areas to identify their role in decision making.