: The focus of the Research Resource at the University of Rochester is to relate the neural codes of the brain to observed behavior. The key feature of neural codes is their slow timescale. The coding of behaviors has to take place within a temporal range of 10-100 milliseconds. It is now believed that computational theory must play the central role in descriptions at this level, but testing its explanatory power requires extensive experimentation. For this reason the Resource is specifically aimed at studying the brain's behaviors at these timescales. This is done using high-performance computers to simulate real-world environments in a way that allows them to be manipulated as a function of behavior. The centerpiece of the constituent laboratories is innovative instrumentation for generating visual and kinetic stimuli in conjunction with the monitoring of behavioral state. Particular emphasis is given to the visual, kinematic, proprioceptive, and haptic states used in sensori-motor coordination. The Resource includes human and animal experiments as well as extensive computer simulations. The Resource equipment is located in three laboratories: (1) A virtual reality laboratory that allows the simultaneous recording of unrestricted head, eye and hand movements while human subjects are engaged in visually-guided tasks using both real and virtual displays. (2) A visual and vestibular stimulation facility for human subjects that uses virtual displays coupled with a sled rotator device capable of delivering precise angular and linear accelerations in any combination. In addition an animal research laboratory for use with awake behaving monkeys has capabilities similar to those described above. (3) An anthropomorphic simulation laboratory that uses robotic hardware and graphics simulation software to simulate sensori-motor coordination. This facility couples an existing high-speed binocular camera control system with an anthropomorphic four-fingered hand. The current proposal would allow the continued development of state-of-the art equipment for psychophysical and neurophysiological measurements as well as improve capabilities with virtual reality simulation. In addition, the proposal would provide necessary resources for expanding the collaboration and service capabilities.
| Rothkopf, Constantin A; Ballard, Dana H (2013) Modular inverse reinforcement learning for visuomotor behavior. Biol Cybern 107:477-90 |
| Huxlin, Krystel R; Martin, Tim; Kelly, Kristin et al. (2009) Perceptual relearning of complex visual motion after V1 damage in humans. J Neurosci 29:3981-91 |
| Jehee, Janneke F M; Ballard, Dana H (2009) Predictive feedback can account for biphasic responses in the lateral geniculate nucleus. PLoS Comput Biol 5:e1000373 |
| Yi, Weilie; Ballard, Dana (2009) RECOGNIZING BEHAVIOR IN HAND-EYE COORDINATION PATTERNS. Int J HR 6:337-359 |
| Rothkopf, Constantin A; Ballard, Dana H (2009) Image statistics at the point of gaze during human navigation. Vis Neurosci 26:81-92 |
| Jehee, Janneke F M; Rothkopf, Constantin; Beck, Jeffrey M et al. (2006) Learning receptive fields using predictive feedback. J Physiol Paris 100:125-32 |
