Abstract. The three-dimensional geometry and connectivity of pore space controls the hydraulic transport behavior of crustal rocks. We report on direct measurement of flow-relevant geometrical properties of the void space in a suite of four samples of Fontainebleau sandstone ranging from 7.5 to 22% porosity. The measurements are obtained from computer analysis of three-dimensional, synchrotron X-ray computed microtomographic images. We present measured distributions of coordination number, channel length, throat size, and pore volume and of correlations between throat size/pore volume and nearest-neighbor pore volume/pore volume determined for these samples. In order to deal with the ambiguity of where a nodal pore ends and a channel begins, we apportion the void space volume solely among nodal pores, with the channel throat surfaces providing the nodal pore delineations. Pore channels thus have length but no associated volume; channel length is defined by nodal pore center to nodal pore center distance. For a sample of given porosity our measurements show that the pore coordination number and throat area are exponentially distributed, whereas the channel length and nodal pore volume follow gamma and lognormal distributions, respectively. Our data indicate an overall increase in coordination number and shortening of pore channel length with increasing porosity. The average coordination number ranges from 3.4 to 3.8; the average channel length ranges from 200 to 130/•m. Average throat area increases from 1600 to 2200/•m 2 with increasing porosity, while average pore volume remains essentially unchanged at around 0.0004 mm a.

The classic ‘size principle’ of motor control describes how increasingly forceful movements arise by the recruitment of motoneurons of progressively larger size and force output into the active pool. Here, we explore the activity of pools of spinal interneurons in larval zebrafish and find that increases in swimming speed are not associated with the simple addition of cells to the active pool. Instead, the recruitment of interneurons at faster speeds is accompanied by the silencing of those driving movements at slower speeds. This silencing occurs both between and within classes of rhythmically-active premotor excitatory interneurons. Thus, unlike motoneurons, there is a continuous shift in the set of cells driving the behavior, even though changes in the speed of the movements and the frequency of the motor pattern appear smoothly graded. We conclude that fundamentally different principles may underlie the recruitment of motoneuron and interneuron pools.

We introduce the medi•l •xis •s • tool in the •nalysis of geometric structure of void sp•ce in porous medi•. The medi•l •xis tr•ces the fundamental geometry of the void p•thw•ys. We describe •n •lgorithm for generating the medi•l •xis of the void structure from digitized three dimensional images of porous medi• obtained from X r•y CAT scans. The medi•l •xis is constructed during •n iterative erosion procedure which, •t e•ch step, replaces the image of the void structure with • smaller version obtained by eroding its surface l•yer of voxels. The •lgorithm is •pplied to high (5 pm) resolution microtomogr•phic images of two rock chips (Berea s•ndstone •nd D•nish chalk) •nd • s•mple of uniform (100 pm) diameter, packed glass beads. We statistically investigate several geometrical properties of the structure of the medial axes obtained. The first is the distribution of relativevolumes in each erosion layer of the void space. We find the distributions to be exponential for the two real rock samples and normal for the packed glass beads. The second property investigated is the distribution of volumes of disconnected segments of the medial axis which are in one-to-one correspondence with disconnected void segments of the sample. We find indications for a universal power law behavior governing the distribution of volumes of the smallest disconnected pieces. The final behavior studied is a geometric tortuosity as measured by shortest paths through the medial axis. This tortuosity distribution appears well described by a gamma distribution.

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