Exploring brain connectivity with two-dimensional neural maps

We introduce two-dimensional neural maps for exploring connectivity in the brain. For this, we create standard streamtube models from diffusion-weighted brain imaging data sets along with neural paths hierarchically projected into the plane. These planar neural maps combine desirable properties of low-dimensional representations, such as visual clarity and ease of tract-of-interest selection, with the anatomical familiarity of 3D brain models and planar sectional views. We distribute this type of visualization both in a traditional stand-alone interactive application and as a novel, lightweight web-accessible system. The web interface integrates precomputed neural-path representations into a geographical digital-maps framework with associated labels, metrics, statistics, and linkouts. Anecdotal and quantitative comparisons of the present method with a recently proposed 2D point representation suggest that our representation is more intuitive and easier to use and learn. Similarly, users are faster and more accurate in selecting bundles using the 2D path representation than the 2D point representation. Finally, expert feedback on the web interface suggests that it can be useful for collaboration as well as quick exploration of data.     

Fabrication and characterization of transducer elements in two-dimensional arrays for medical ultrasound imaging

Some of the problems of developing a two-dimensional (2-D) transducer array for medical imaging are examined. The fabrication of a 2-D array material consisting of lead zirconate titanate (PZT) elements separated by epoxy is discussed. Ultrasound pulses and transmitted radiation patterns from individual elements in the arrays are measured. A diffraction theory for the continuous wave pressure field of a 2-D array element is generalized to include both electrical and acoustical cross-coupling between elements. This theory can be fit to model the measured radiation patterns of 2-D array elements, giving an indication of the level of cross-coupling in the array, and the velocity of the acoustic cross-coupling wave. Improvements in bandwidth and cross-coupling resulting from the inclusion of a front acoustic matching layer are demonstrated, and the effects of including a lossy backing material on the array are discussed. A broadband electrical matching network is described, and pulse-echo waveforms and insertion loss from a 2-D array element are measured.     

Effects of low-voltage electrical stimulation during exsanguination on meat quality and display colour stability

Five steers from each of four slaughter groups were randomly assigned to a low-voltage electrical stimulation (LVES) treatment during exsanguination (within 5 min after stunning) and five served as controls (C). LVES consisted of 50V of 60 Hz alternating current (1 s on and 1 s off for 2 min).

At 28 h, LVES longissimus (LM) was lighter in colour, softer, coarser in texture and tended to have lower marbling estimates than C. LVES LM steaks were lighter red at 0 and 1 days, but more discoloured at 5 days, of display than C steaks. Both the deep (DSM) and superficial (SSM) portions of LVES semimembranosus (SM) steaks were lighter red at 0 and 1 days of display than C steaks. Water-holding capacity for LVES LM and DSM steaks was lower than for C steaks. A trained sensory panel found LVES LM steaks to be less juicy and less tender than C steaks. Also, LVES LM steaks had greater cooking losses than C steaks in two of the four slaughter groups. We conclude that LVES during exsanguination, coupled with relatively slow initial chilling, may be detrimental to muscle quality.     

Inferring the capacity of the vector Poisson channel with a Bernoulli model

The capacity defines the ultimate fidelity limits of information transmission by any system. We derive the capacity of parallel Poisson process channels to judge the relative effectiveness of neural population structures. Because the Poisson process is equivalent to a Bernoulli process having small event probabilities, we infer the capacity of multi-channel Poisson models from their Bernoulli surrogates. For neural populations wherein each neuron has individual innervation, inter-neuron dependencies increase capacity, the opposite behavior of populations that share a single input. We use Shannon's rate-distortion theory to show that for Gaussian stimuli, the mean-squared error of the decoded stimulus decreases exponentially in both the population size and the maximal discharge rate. Detailed analysis shows that population coding is essential for accurate stimulus reconstruction. By modeling multi-neuron recordings as a sum of a neural population, we show that the resulting capacity is much less than the population's, reducing it to a level that can be less than provided with two separated neural responses. This result suggests that attempting neural control without spike sorting greatly reduces the achievable fidelity. In contrast, single-electrode neural stimulation does not incur any capacity deficit in comparison to stimulating individual neurons.     

Physics-based visualization of dense natural clouds. I. Three-dimensional discrete ordinates radiative transfer

A technique is developed to model radiative transfer in three-dimensional natural clouds with a standard discrete ordinates finite-element method modified to evaluate cell-surface-averaged radiances. A log-least-squares-based scale transformation is used to improve the discrete phase-function model. We handle dense media by assuming constant diffuse radiances over input faces to cubic cells, allowing analytical forms for transmittance factors. Transmission equations are combined with diffuse volumetric single-scattering calculations to support evaluations of cell energy balance. Energy not accounted for volumetrically is treated with surface-based effects. Results produced show accurate flux computations at over 30 optical depths per modeled cell. Comparisons with nonuniform cloud Monte Carlo calculations show less than 1% rms error and correlations greater than 0.999 for cases in which cloud-density fluctuations are resolved.     

Design and fabrication of a diffractive phase element for wavelength demultiplexing and spatial focusing simultaneously

The design of a diffractive phase element (DPE) that simultaneously implements wavelength demultiplexing and focusing is carried out on the basis of the general theory of amplitude-phase retrieval. The designed DPE is fabricated with optical contact lithography. Three masks are needed to produce the surface-relief structure of the DPE with eight quantized levels in depths. Experiments demonstrate that the designed DPE can successfully implement both the functions of demultiplexing three different-wavelength beams and focusing each component at a predesignated position simultaneously. Experimental measurements are in good agreement with the results of numerical simulations.