Functional impact of cerebral connections

Cerebral networks are complex sets of connections that resemble a ladder-like web of multiple parallel feedforward, lateral, and feedback connections. This static anatomical description has been pivotal in guiding our understanding of signal processing within cerebral networks. However, measures on both magnitude and functional significance of connections are extremely limited. Here, we compare the anatomically defined strengths of a set of cerebral pathways emerging from the visual middle suprasylvian (MS) cortex of the cat with measures of the functional impact the same region has over distant sites. These functional measures were obtained by analyzing the local and distant effects of MS cooling deactivation on deoxyglucose uptake. Relative to major efferent projections from MS cortex that have a strong influence, projections to early visual processing stages have weaker functional influences than predicted from the anatomy. For higher processing stages, the converse holds: projections from MS cortex have stronger functional influence than predicted from the anatomy. We conclude that these and future functional measures, obtained using the same combination of techniques, will furnish fundamental, new information that complements and extends current models of static cerebral networks, and lead to more realistic models of cerebral network function and component interactions.

Rock friction and its implications for earthquake prediction examined via models of Parkfield earthquakes.

The friction of rocks in the laboratory is a function of time, velocity of sliding, and displacement. Although the processes responsible for these dependencies are unknown, constitutive equations have been developed that do a reasonable job of describing the laboratory behavior. These constitutive laws have been used to create a model of earthquakes at Parkfield, CA, by using boundary conditions appropriate for the section of the fault that slips in magnitude 6 earthquakes every 20-30 years. The behavior of this model prior to the earthquakes is investigated to determine whether or not the model earthquakes could be predicted in the real world by using realistic instruments and instrument locations. Premonitory slip does occur in the model, but it is relatively restricted in time and space and detecting it from the surface may be difficult. The magnitude of the strain rate at the earth's surface due to this accelerating slip seems lower than the detectability limit of instruments in the presence of earth noise. Although not specifically modeled, microseismicity related to the accelerating creep and to creep events in the model should be detectable. In fact the logarithm of the moment rate on the hypocentral cell of the fault due to slip increases linearly with minus the logarithm of the time to the earthquake. This could conceivably be used to determine when the earthquake was going to occur. An unresolved question is whether this pattern of accelerating slip could be recognized from the microseismicity, given the discrete nature of seismic events. Nevertheless, the model results suggest that the most likely solution to earthquake prediction is to look for a pattern of acceleration in microseismicity and thereby identify the microearthquakes as foreshocks.

Toward an outline of the topography of a realistic protein-folding funnel.

Experimental information on the structure and dynamics of molten globules gives estimates for the energy landscape's characteristics for folding highly helical proteins, when supplemented by a theory of the helix-coil transition in collapsed heteropolymers. A law of corresponding states relating simulations on small lattice models to real proteins possessing many more degrees of freedom results. This correspondence reveals parallels between "minimalist" lattice results and recent experimental results for the degree of native character of the folding transition state and molten globule and also pinpoints the needs of further experiments.