Dr. Olaf SpornsThe NewScientist.com article Vision-body link tested in robot experiments said
Experiments involving real and simulated robots suggest that the relationship between physical movement and sensory input could be crucial to developing more intelligent machines.
Tests involving two real and one simulated robot show that feedback between sensory input and body movement is crucial to navigating the surrounding world. Understanding this relationship better could help scientists build more life-like machines, say the researchers involved.
Scientists studying artificial intelligence have traditionally separated physical behaviour and sensory input. “But the brain’s inputs are not independent,” says Olaf Sporns, a neuroscientist at Indiana University, US. “For example, motor behaviour has a role to play in what the body senses from the environment.”
Associate Professor, Department of Psychology, Programs in Neural
Science and Cognitive Science, at the
Biocomplexity Institute, Indiana
Olaf was born in Kiel, Germany. After studying biochemistry at the University of Tüingen in Germany, he entered the Graduate Program at New York’s Rockefeller University. In 1990, he received a Ph.D. in neuroscience and became a Senior Fellow in Theoretical Neurobiology at The Neurosciences Institute in New York and San Diego. Since 2000, he has held a faculty position at the Department of Psychology at Indiana University in Bloomington. He is currently an Associate Professor of Psychology, as well as a core member of the Programs in Cognitive Science and Neuroscience, and directs the Computational Cognitive Neuroscience Laboratory.
His main research field is theoretical and computational neuroscience. A main research focus is the design of neuronal models that can be interfaced with autonomous robots and can be used to study neurobiological and cognitive functions such as perceptual categorization, sensorimotor development, and the development of neuronal receptive field properties. Another focus is the design of anatomically and physiologically detailed models of neuronal networks to investigate the large-scale dynamics of neuronal populations. This work includes the development of statistical measures for characterizing complexity in neuronal networks as well as methods for analyzing the topological structure of neuronal connectivity patterns.
He is a member of the AAAS, the Society for Neuroscience, the International Society for Adaptive Behavior, the Cognitive Neuroscience Society and Sigma Xi. He is an associate editor or member of the editorial board of the journals BioSystems, Adaptive Behavior, the International Journal of Humanoid Robotics, the Journal of Integrative Neuroscience, and Neuroinformatics.
Olaf coauthored Theoretical Neuroanatomy: Relating Anatomical and Functional Connectivity in Graphs and Cortical Connection Matrices, Autonomous mental development by robots and animals, Measuring information integration, Organization, development and function of complex brain networks, Motifs in brain networks, Neuromodulation and plasticity in an autonomous robot, The human connectome: A structural description of the human brain, and A Large-scale Neurocomputational Model of Task-oriented Behavior Selection and Working Memory in Prefrontal Cortex. Read his full list of publications!
Watch his Monad robot approaching and “tasting” a red (appetitive) object. Watch Monad’s behavior when encountering a blue (aversive) object. Note that the object is dropped as soon as the taste signal is received. Watch how Monad’s behavior has changed with learning. Now, the color of the object has become predictive of the aversive taste and, consequently, the avoidance response is triggered by the visual input alone. Read When Robots See Red.