What you feel is what you see: inverse dynamics estimation underlies the resistive sensation of a delayed cursor

How our central nervous system (CNS) learns and exploits relationships between force and motion is a fundamental issue in computational neuroscience. While several lines of evidence have suggested that the CNS predicts motion states and signals from motor commands for control and perception (forward dynamics), it remains controversial whether it also performs the ‘inverse’ computation, i.e. the estimation of force from motion (inverse dynamics). Here, we show that the resistive sensation we experience while moving a delayed cursor, perceived purely from the change in visual motion, provides evidence of the inverse computation. To clearly specify the computational process underlying the sensation, we systematically varied the visual feedback and examined its effect on the strength of the sensation. In contrast to the prevailing theory that sensory prediction errors modulate our perception, the sensation did not correlate with errors in cursor motion due to the delay. Instead, it correlated with the amount of exposure to the forward acceleration of the cursor. This indicates that the delayed cursor is interpreted as a mechanical load, and the sensation represents its visually implied reaction force. Namely, the CNS automatically computes inverse dynamics, using visually detected motions, to monitor the dynamic forces involved in our actions.     

暗示性运动加工的认知神经机制

暗示性运动是指个体观看静止图片时从中知觉到的运动.研究者采用高低认知水平两类暗示性运动刺激材料,借助"冻结帧"、直接观看、运动后效和f MRI适应等任务范式,探讨了注意和意识在暗示性运动加工中的作用及其记忆特点;并借助脑成像等技术,考察了颞中区、颞上皮层区、颞上沟、镜像神经元系统等脑区在暗示性运动加工中的作用.但由于暗示性运动加工涉及"视觉腹侧通路与背侧通路功能的分离与整合"问题,目前对相关研究结果和解释还存在争议,暗示性运动加工的认知神经机制仍有待于进一步研究.     

Seasonal differences in the effects of oscillatory and uni‐directional flow on the growth and nitrate‐uptake rates of juvenile Laminaria digitata (Phaeophyceae)

The influence of oscillatory versus unidirectional flow on the growth and nitrate‐uptake rates of juvenile kelp, Laminaria digitata, was determined seasonally in experimental treatments that simulated as closely as possible natural environmental conditions. In winter, regardless of flow condition (oscillatory and unidirectional) or water velocity, no influence of water motion was observed on the growth rate of L. digitata. In summer, when ambient nitrate concentrations were low, increased water motion enhanced macroalgal growth, which is assumed to be related to an increase in the rate of supply of nutrients to the blade surface. Nitrate‐uptake rates were significantly influenced by water motion and season. Lowest nitrate‐uptake rates were observed for velocities <5 cm · s^?1 and nitrate‐uptake rates increased by 20%–50% under oscillatory motion compared to unidirectional flow at the same average speed. These data further suggested that the diffusion boundary layer played a significant role in influencing nitrate‐uptake rates. However, while increased nitrate‐uptake in oscillatory flow was clear, this was not reflected in growth rates and further work is required to understand the disconnection of nitrate‐uptake and growth by L. digitata in oscillatory flow. The data obtained support those from related field‐based studies, which suggest that in summer, when insufficient nitrogen is available in the water to saturate metabolic demand, the growth rate of kelps will be influenced by water motion restricting mass transfer of nitrogen.     

Phylogenetic eigenvectors and nonstationarity in the evolution of theropod dinosaur skulls

Despite the long‐standing interest in nonstationarity of both phenotypic evolution and diversification rates, only recently have methods been developed to study this property. Here, we propose a methodological expansion of the phylogenetic signal‐representation (PSR) curve based on phylogenetic eigenvectors to test for nonstationarity. The PSR curve is built by plotting the coefficients of determination R² from phylogenetic eigenvector regression (PVR) models increasing the number of phylogenetic eigenvectors against the accumulated eigenvalues. The PSR curve is linear under a stationary model of trait evolution (i.e. the Brownian motion model). Here we describe the distribution of shifts in the models R² and used a randomization procedure to compare observed and simulated shifts along the PSR curve, which allowed detecting nonstationarity in trait evolution. As an applied example, we show that the main evolutionary pattern of variation in the theropod dinosaur skull was nonstationary, with a significant shift in evolutionary rates in derived oviraptorosaurs, an aberrant group of mostly toothless, crested, birdlike theropods. This result is also supported by a recently proposed Bayesian‐based method (AUTEUR). A significant deviation between Ceratosaurus and Limusaurus terminal branches was also detected. We purport that our new approach is a valuable tool for evolutionary biologists, owing to its simplicity, flexibility and comprehensiveness.     

Mechanical resolution of chiral objects in achiral media: Where is the size limit?

Macroscopic chiral objects (boats and planes with turned rudders, shoes, etc.) get separated from their mirror‐image counterparts by motion in achiral media. However, chiral molecules are not enantio‐differentiated without the presence of a chiral environment, which may be due to other chiral molecules in the medium. This article explores the reasons of this micro/macro difference as well as the size borderline between the two regimes. There are two major demarcation lines, both related to the object's chaotic thermal motion. The first one is due to destruction of the necessary spatial orientation by the fast rotational diffusion. Only particles larger than 1 μm can maintain their original orientation for 1 sec or longer. For smaller particles, an additional external orienting factor, e.g., a strong electric field has to be applied. The second limitation is defined by the ratio of the hydrodynamic separation of the enantiomers (which is directly proportional to time) to their displacement due to the translational Brownian motion (which is proportional to square root of time). On the laboratory time scales (up to a year), the chiral objects have to be larger than 0.25 μm to be resolved. On evolutionary time scales, much smaller object could be resolved. For enantiomers approaching the molecular size, periods comparable to the age of the universe would be required. Chirality, 2011. © 2010 Wiley‐Liss, Inc.     

Trifluoperazine regulation of calmodulin binding to Fas: a computational study

Death-inducing signaling complex (DISC) formation is a critical step in Fas-mediated signaling for apoptosis. Previous experiments have demonstrated that the calmodulin (CaM) antagonist, trifluoperazine (TFP) regulates CaM-Fas binding and affects Fas-mediated DISC formation. In this study, we investigated the anti-cooperative characteristics of TFP binding to CaM and the effect of TFP on the CaM-Fas interaction from both structural and thermodynamic perspectives using combined molecular dynamics simulations and binding free energy analyses. We studied the interactions of different numbers of TFP molecules with CaM and explored the effects of the resulting conformational changes in CaM on CaM-Fas binding. Results from these analyses showed that the number of TFP molecules bound to CaM directly influenced α-helix formation and hydrogen bond occupancy within the α-helices of CaM, contributing to the conformational and motion changes in CaM. These changes affected CaM binding to Fas, resulting in secondary structural changes in Fas and conformational and motion changes of Fas in CaM-Fas complexes, potentially perturbing the recruitment of Fas-associated death domain for DISC formation. The computational results from this study reveal the structural and molecular mechanisms that underlie the role of the CaM antagonist, TFP, in regulation of CaM-Fas binding and Fas-mediated DISC formation in a concentration-dependent manner.     

Carnivorous Utricularia: The buckling scenario

We review recent results about the functioning of aquatic carnivorous traps from the genus Utricularia. The use of high speed cameras has helped to elucidate the mechanism at the origin of the ultra fast capture process of Utricularia, at a millisecond time scale. As water is pumped out of the trap, pressure decreases inside the trap and elastic energy is stored due to the change of shape of the trap body. This energy is suddenly released when the trap is fired: the trap door undergoes an elastical instability: buckling, which allows its fast and passive opening and closure. This mechanism is used by Utricularia both to catch preys touching its trigger hairs and to fire spontaneously at regular time intervals. The results leading to this interpretation are reviewed and discussed and suggestions for further work are briefly presented.     

Calculating spatial statistics for velocity jump processes with experimentally observed reorientation parameters

Mathematical modelling of the directed movement of animals, microorganisms and cells is of great relevance in the fields of biology and medicine. Simple diffusive models of movement assume a random walk in the position, while more realistic models include the direction of movement by assuming a random walk in the velocity. These velocity jump processes, although more realistic, are much harder to analyse and an equation that describes the underlying spatial distribution only exists in one dimension. In this communication we set up a realistic reorientation model in two dimensions, where the mean turning angle is dependent on the previous direction of movement and bias is implicitly introduced in the probability distribution for the direction of movement. This model, and the associated reorientation parameters, is based on data from experiments on swimming microorganisms. Assuming a transport equation to describe the motion of a population of random walkers using a velocity jump process, together with this realistic reorientation model, we use a moment closure method to derive and solve a system of equations for the spatial statistics. These asymptotic equations are a very good match to simulated random walks for realistic parameter values.