Near optimal combination of sensory and motor uncertainty in time during a naturalistic perception-action task.

Most behavioral tasks have time constraints for successful completion, such as catching a ball in flight. Many of these tasks require trading off the time allocated to perception and action, especially when only one of the two is possible at any time. In general, the longer we perceive, the smaller the uncertainty in perceptual estimates. However, a longer perception phase leaves less time for action, which results in less precise movements. Here we examine subjects catching a virtual ball. Critically, as soon as subjects began to move, the ball became invisible. We study how subjects trade-off sensory and movement uncertainty by deciding when to initiate their actions. We formulate this task in a probabilistic framework and show that subjects' decisions when to start moving are statistically near optimal given their individual sensory and motor uncertainties. Moreover, we accurately predict individual subject's task performance. Thus we show that subjects in a natural task are quantitatively aware of how sensory and motor variability depend on time and act so as to minimize overall task variability.

Structure learning in action.

'Learning to learn' phenomena have been widely investigated in cognition, perception and more recently also in action. During concept learning tasks, for example, it has been suggested that characteristic features are abstracted from a set of examples with the consequence that learning of similar tasks is facilitated-a process termed 'learning to learn'. From a computational point of view such an extraction of invariants can be regarded as learning of an underlying structure. Here we review the evidence for structure learning as a 'learning to learn' mechanism, especially in sensorimotor control where the motor system has to adapt to variable environments. We review studies demonstrating that common features of variable environments are extracted during sensorimotor learning and exploited for efficient adaptation in novel tasks. We conclude that structure learning plays a fundamental role in skill learning and may underlie the unsurpassed flexibility and adaptability of the motor system.

Coral health and disease in the Pacific: vision for action

Shallow coral reefs in the IndoPacific contain the highest diversity of marine organisms in the world, with approximately 1500 described species of fish, over 500 species of scleractinian corals, and an estimated 1-10 million organisms yet to be characterized (Reaka-Kudla et al. 1994). These centers of marine biodiversity are facing significant, multiple threats to reef community and habitat structure and function, resulting in local to wide-scale regional damage. Wilkinson (2004) characterized the major pressures as including (1) global climate change, (2) diseases, plagues and invasive species, (3) direct human pressures, (4) poor governance and lack of political will, and (5) international action or inaction. Signs that the natural plasticity of reef ecosystems has been exceeded in many areas from the effects of environmental (e.g., global climate change) and anthropogenic (e.g., land use, pollution) stressors is evidenced by the loss of 20% of the world’s coral reefs (Wilkinson 2004). Predictions are that another 24% (Wilkinson 2006) are under imminent risk of collapse and an additional 26% are under a longer term threat from reduced fitness, disease outbreaks, and increased mortality. These predictions indicate that the current list of approximately 30-40 fatal diseases impacting corals will expand as will the frequency and extent of “coral bleaching” (Waddell 2005; Wilkinson 2004). Disease and corallivore outbreaks, in combination with multiple, concomitant human disturbances are compromising corals and coral reef communities to the point where their ability to rebound from natural disturbances is being lost.