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Since its discovery.sup.1,2, the deep-sea glass sponge Euplectella aspergillum has attracted interest in its mechanical properties and beauty. Its skeletal system is composed of amorphous hydrated silica and is arranged in a highly regular and hierarchical cylindrical lattice that begets exceptional flexibility and resilience to damage.sup.3-6. Structural analyses dominate the literature, but hydrodynamic fields that surround and penetrate the sponge have remained largely unexplored. Here we address an unanswered question: whether, besides improving its mechanical properties, the skeletal motifs of E. aspergillum underlie the optimization of the flow physics within and beyond its body cavity. We use extreme flow simulations based on the 'lattice Boltzmann' method.sup.7, featuring over fifty billion grid points and spanning four spatial decades. These in silico experiments reproduce the hydrodynamic conditions on the deep-sea floor where E. aspergillum lives.sup.8-10. Our results indicate that the skeletal motifs reduce the overall hydrodynamic stress and support coherent internal recirculation patterns at low flow velocity. These patterns are arguably beneficial to the organism for selective filter feeding and sexual reproduction.sup.11,12. The present study reveals mechanisms of extraordinary adaptation to live in the abyss, paving the way towards further studies of this type at the intersection between fluid mechanics, organism biology and functional ecology. High-performance hydrodynamic simulations show that the skeletal structure of the deep-sea sponge Euplectella aspergillum reduces the hydrodynamic stresses on it, while possibly being beneficial for feeding and reproduction., Author(s): Giacomo Falcucci [sup.1] [sup.2] , Giorgio Amati [sup.3] , Pierluigi Fanelli [sup.4] , Vesselin K. Krastev [sup.1] , Giovanni Polverino [sup.5] , Maurizio Porfiri [sup.6] [sup.7] [sup.8] , Sauro [...]

Computational models of arterial growth and remodeling promise to increase our understanding of basic biological processes, such as development, tissue maintenance, and aging, the biomechanics of functional adaptation, the progression and treatment of disease, responses to injuries, and even the design of improved replacement vessels and implanted medical devices. Ensuring reliability of and confidence in such models requires appropriate attention to verification and validation, including parameter sensitivity studies. In this paper, we classi different types of parameters within a constrained mature model of arterial growth and remodeling; we then evaluate the sensitivity of model predictions to parameter values that are not known directly from experiments ,for cases of modest sustained alterations in blood flow and pressure as well as increased axial extension. Particular attention is directed toward complementary roles of smooth muscle vasoactivity and matrix turnover, with an emphasis on mechanosensitive changes in the rates of turnover of intramural fibrillar collagen and smooth muscle in maturity. It is shown that vasoactive changes influence the rapid change in caliber that is needed to maintain wall shear stress near its homeostatic level and the longer term changes in wall thickness that are needed to maintain circumferential wall stress near its homeostatic target. Moreover, it is shown that competing effects of intramural and wall shear stress-regulated rates of turnover can develop complex coupled responses. Finally, results demonstrate that the sensitivity to parameter values depends upon the type of perturbation from normalcy, with changes in axial stretch being most sensitive consistent with empirical reports. [DOI: 10.1115/1.3192144] Keywords: vasoactivity, stress, collagen turnover, verification, experimental design

Speech comprehension is resistant to acoustic distortion in the input, reflecting listeners' ability to adjust perceptual processes to match the speech input. This adjustment is reflected in improved comprehension of distorted speech with experience. For noise vocoding, a manipulation that removes spectral detail from speech, listeners' word report showed a significantly greater improvement over trials for listeners that heard clear speech presentations before rather than alter hearing distorted speech (clear-then-distorted compared with distorted-then-clear feedback, in Experiment 1 ). This perceptual learning generalized to untrained words suggesting a sublexical locus for learning and was equivalent for word and nonword training stimuli (Experiment 2). These findings point to the crucial involvement of phonological short-term memory and top-down processes in the perceptual learning of noise-vocoded speech. Similar processes may facilitate comprehension of speech in an unfamiliar accent or following cochlear implantation. Keywords: speech, perception, adaptation, vocoding

Neural models are needed at many levels, ranging from the biophysically based to connectionist abstractions. The adjustable pattern generator (APG) model of the cerebellum discussed in the target article by Houk, Buckingham, and Barto operates at an intermediate level and is constrained by a large body of anatomical and physiological data. The associative memory model originally proposed by Marr (1969) and Albus (1971) on the basis of the microcircuitry of the cerebellar cortex is still relevant today, although it needs to be coupled to the problem of motor pattern generation. In considering the problem of cerebellar learning, one needs some source of training information to adjust network performance so that it performs fruitful interactions with the environment; however, it is not true that this 'teacher' needs to be particularly smart. We address these and other important issues raised by the commentators.

The basic concepts employed in formulating models of the process of stress adaptation in living bone tissue are reviewed. A purpose of this review is to define and separate issues in the formulation of bone remodeling theories. After discussing the rationale and objective of these models, the concepts and techniques involved in the modeling process are reviewed one by one. It is concluded that some techniques will be more successful than others in achieving the goals of computational bone remodeling. In particular, rationale is given for the preference of surface bone remodeling approaches over internal bone remodeling approaches, and for interactive multi-scale level, rather than mono-scale level, computational strategies.

Remodeling of tissue in response to physical stress is a very complex process. The changes in the stimulus (cause) and response (effect) must be measured and the results must be organized into mathematical forms that are suitable for predictions and applications. An experiment where the stimulus (pressure, flow, shear stress, etc.) can be changed approximately as a step function (a step plus a perturbation) and the response (structure, material properties, function, etc.), which can be measured over time, can be simulated by indicial response functions (IRFs). The IRF is a mathematical expression of the ratio of the change in a particular feature of the system in response to a unit step change in stimulus. The IRF approach provides a quantitative description of the remodeling process, simplifies the interpretation of data, and greatly increases the potential of using the experimental data for prediction of the outcome for future experiments. The objective of this review is to provide an overview of the IRF approach including some exemplary systems. The goal is to illustrate how the indicial expressions make it possible to integrate biological complexity by convolution. The time courses of stimuli represent half of the convolution while the time course of changes in response represents the second half of the convolution. The IRF approach provides an understanding of the physiological problems with mathematical accuracy and may be conducive to new findings. [DOI: 10.1115/1.3200909]

To understand adaptation (and exaptation), a more comprehensive view of development is required: one beyond a constraining force. Developmental plasticity may be an adaptation by natural selection simultaneously favored (or sometimes in conflict) at multiple levels of biological organization (e.g., cells, individuals, groups, etc.). To understand the interrelationships between developmental plasticity and adaptive evolution I borrow heavily from West-Eberhard (2003) and Frank (1995; 1997). Developmental plasticity facilitates evolution, results in particular patterns of evolutionary change, and may produce exaptations by design rather than by chance.

The adjustable pattern generator (APG) model addresses physiological detail in a manner that renders it eminently testable. However, the problem for which the APG was developed, namely, limb control, may be computationally too complex for this purpose. Instead, it is proposed that recent empirical and theoretical advances in understanding the role of the cerebellum in low-level saccadic control could be used to refine and extend the APG.

The present commentary considers the question of what must be learned in different types of motor skills, thereby limiting the question of what should be adjusted in the APG model in order to explain successful learning. It is concluded that an open loop model like the APG might well be able to describe the learning pattern of motor skills in a stable, predictable environment. Recent research on saccadic plasticity, however, illustrates that motor skills performed in an unpredictable environment depend heavily on sensory (mostly visual) feedback.