Paul Cisek is an associate professor at the department of physiology at the University of Montréal. After obtaining a B.Sc. in computer science from the Rochester Institute of Technology in 1991 and working briefly at Microsoft, he became interested in pursuing an academic career in the brain sciences. He enrolled at the computational neuroscience program at Boston University, where he worked with Drs. Stephen Grossberg and Daniel Bullock, two pioneers in the field of neural networks. After obtaining his Ph.D. in 1997, he sought to complement his theoretical experience with experimental work in cortical neurophysiology.
In his postdoctoral studies he worked with Dr. Steve Scott at Queen’s University, studying the neural mechanisms of motor control, and later with Dr. John Kalaska at the University of Montréal, studying the cortical mechanisms of planning and decision-making. In 2004 he joined the faculty of the University of Montréal where he has established a lab studying decision-making and movement planning using computational modeling, psychophysics, transcranial magnetic stimulation, and multi-electrode recording in the cerebral cortex.
Moving beyond the computer metaphor for the brain
A central concept in modern efforts to understand human intelligence is the idea that brains are information processing systems, which use sensory input to build perceptual representations and knowledge of the world, store and retrieve memories, make decisions, and plan and execute actions. However, the results of many neurophysiological studies are not compatible with this classic and influential view. Instead, I will argue that the brain should be seen within its evolutionary context – as a control system for interacting with the world – and will discuss the implications of this notion for understanding brains and simulating them in machines.