Finley, James
Associate Professor of Biokinesiology and Physical Therapy
In the USC Locomotor Control Lab, we seek to understand how walking is controlled and adapted in both the healthy and injured neuromuscular systems. We develop models and experiments based on principles of neuroscience, biomechanics, engineering, and exercise physiology to identify the factors that guide locomotor learning and rehabilitation. Ultimately, the goal of our work is to design novel and effective interventions to improve walking ability in individuals with damage to the nervous system.
Itti, Laurent
Professor of Computer Science and Psychology
The main fundamental research focus of the lab is in using computational modeling to gain insight into biological brain function. Thus, we study biologically-plausible brain models, and we compare the predictions of model simulations to empirical measurements from living systems. The brain subsystem towards which most of our efforts are focused is the visual system. Our modeling efforts range from fairly detailed models of small neuronal circuits, such as a single hypercolumn of orientation-selective neurons in primary visual cortex, to large-scale models embodying several million highly-simplified neurons to explore mechanisms of visual attention, gaze control, object recognition, and goal-oriented scene understanding. Further, we strive to employ modeling principles which are mathematically optimal in some task- and goal-dependent sense. Thus, we are interested in investigating the tasks and conditions for which the biological brain approaches the theoretical limits of information processing.
Mel, Bartlett
Associate Professor of Biomedical Engineering
Our research involves the use of computer models to study brain function. Some of our goals are of a primarily scientific nature. For example, we use detailed biophysiical modeling to study synaptic integration in active dendritic trees, and explore how dendritic trees could contribute to the sensory and memory-related functions of nerve cells. Some of our work combines scientific and engineering goals. For example, we have modeled the complex computations carried out in the visual cortex that allow us to recognize objects with remarkable speed, accuracy, and robustness -- far beyond the technical state of the art. Our overarching goal is to use insights gained from this work to help in the construction of next-generation intelligent machines.
Piray, Payam
Assistant Professor of Psychology
How do people make sense of incomplete and noisy observations? How do humans make decisions in an uncertain world and how do they learn from their mistakes? We investigate these problems in health and disease using computational and experimental tools.
Schweighofer, Nicolas
Professor of Biokinesiology and Physical Therapy
Nicolas Schweighofer is a professor of biokinesiology and physical therapy and holds joint appointments in computer science, biomedical engineering and neuroscience at USC. He is also the director of the Center for Statistics and Computation in Biokinesiology. He co-founded computational neurorehabilitation, an emerging field at the intersection of neurorehabilitation, computational neuroscience, motor control and learning, and artificial intelligence (AI). The overarching goals of computational neurorehabilitation are to understand and to further improve motor recovery following neurologic injury by mathematically modeling and simulating the neural processes underlying the change in behavior due to rehabilitation. In his current research, he is investigating how predictive models of recovery, informed by the neuroscience of stroke recovery and motor learning, as well as large datasets, can provide the basis for AI methods that suggest timing, dosage and content of rehabilitation. Such an approach will transform neurorehabilitation by guiding clinicians, patients and healthcare providers in the optimization of treatments via precision rehabilitation.
