To be or not to be? What molecules say about Runcina brenkoae Thompson, 1980 (Gastropoda: Heterobranchia: Runcinida)

Runcinids are poorly known minute marine slugs inhabiting intertidal and shallow subtidal rocky shores. Among the European species, Runcina brenkoae, described from the Adriatic Sea in the Mediterranean, has been described to display chromatic variability, placing in question the true identity and geographic distribution of the species. In this paper we investigate the taxonomic status of R. brenkoae based on specimens from the central and western Mediterranean Sea and the southern Iberian coastline of Portugal and Spain, following an integrative approach combining multi-locus molecular phylogenetics based on the mitochondrial markers cytochrome c oxidase subunit I and 16S rRNA and the nuclear gene histone H3, together with the study of morpho-anatomical characters investigated by scanning electron microscopy. To aid in species delimitation, the Automatic Barcode Gap Discovery and Bayesian Poisson tree process methods were employed. Our results indicate the existence of a complex of three species previously identified as R. brenkoae, namely two new species here described (R. marcosi n. sp. and R. lusitanica n. sp.) and R. brenkoae proper

Deliberation in the motor system: Reflex gains track evolving evidence leading to a decision

Contains fulltext : 102420.pdf (publisher's version ) (Open Access)Both decision making and sensorimotor control require real-time processing of noisy information streams. Historically these processes were thought to operate sequentially: cognitive processing leads to a decision, and the outcome is passed to the motor system to be converted into action. Recently, it has been suggested that the decision process may provide a continuous flow of information to the motor system, allowing it to prepare in a graded fashion for the probable outcome. Such continuous flow is supported by electrophysiology in nonhuman primates. Here we provide direct evidence for the continuous flow of an evolving decision variable to the motor system in humans. Subjects viewed a dynamic random dot display and were asked to indicate their decision about direction by moving a handle to one of two targets. We probed the state of the motor system by perturbing the arm at random times during decision formation. Reflex gains were modulated by the strength and duration of motion, reflecting the accumulated evidence in support of the evolving decision. The magnitude and variance of these gains tracked a decision variable that explained the subject's decision accuracy. The findings support a continuous process linking the evolving computations associated with decision making and sensorimotor control.11 p

Overcoming time delays in visuomotor control

SIGLEAvailable from British Library Document Supply Centre- DSC:D176446 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Learning multiple models of non-linear dynamics for control under varying contexts

Abstract. For stationary systems, efficient techniques for adaptive motor control exist which learn the system’s inverse dynamics online and use this single model for control. However, in realistic domains the system dynamics often change depending on an external unobserved context, for instance the work load of the system or contact conditions with other objects. A solution to context-dependent control is to learn multiple inverse models for different contexts and to infer the current context by analyzing the experienced dynamics. Previous multiple model approaches have only been tested on linear systems. This paper presents an efficient multiple model approach for non-linear dynamics, which can bootstrap context separation from context-unlabeled data and realizes simultaneous online context estimation, control, and training of multiple inverse models. The approach formulates a consistent probabilistic model used to infer the unobserved context and uses Locally Weighted Projection Regression as an efficient online regressor which provides local confidence bounds estimates used for inference.

Learning Problem Solving Skills from Demonstration: An Architectural ApproachArtificial General Intelligence

We present an architectural approach to learning problem solving skills from demonstration, using internal models to represent problem-solving operational knowledge. Internal forward and inverse models are initially learned through active interaction with the environment, and then enhanced and finessed by observing expert teachers. While a single internal model is capable of solving a single goal-oriented task, it is their sequence that enables the system to hierarchically solve more complex task. Activation of models is goal-driven, and internal "mental" simulations are used to predict and anticipate future rewards and perils and to make decisions accordingly. In this approach intelligent system behavior emerges as a coordinated activity of internal models over time governed by sound architectural principles. In this paper we report preliminary results using the game of Sokoban, where the aim is to learn goal-oriented patterns of model activations capable of solving the problem in various contexts

Sensorimotor integration compensates for visual localization errors during smooth pursuit eye movements

To localize a seen object, the CNS has to integrate the object's retinal location with the direction of gaze. Here we investigate this process by examining the localization of static objects during smooth pursuit eye movements. The normally experienced stability of the visual world during smooth pursuit suggests that the CNS essentially compensates for the eye movement when judging target locations. However, certain systematic localization errors are made, and we use these to study the process of sensorimotor integration. During an eye movement, a static object's image moves across the retina. Objects that produce retinal slip are known to be mislocalized: objects moving toward the fovea are seen too far on in their trajectory, whereas errors are much smaller for objects moving away from the fovea. These effects are usually studied by localizing the moving object relative to a briefly flashed one during fixation: moving objects are then mislocalized, but flashes are not. In our first experiment, we found that a similar differential mislocalization occurs for static objects relative to flashes during pursuit. This effect is not specific for horizontal pursuit but was also found in other directions. In a second experiment, we examined how this effect generalizes to positions outside the line of eye movement. We found that large localization errors were found in the entire hemifield ahead of the pursuit target and were predominantly aligned with the direction of eye movement. In a third experiment, we determined whether it is the flash or the static object that is mislocalized ahead of the pursuit target. In contrast to fixation conditions, we found that during pursuit it is the flash, not the static object, which is mislocalized. In a fourth experiment, we used egocentric localization to confirm this result. Our results suggest that the CNS compensates for the retinal localization errors to maintain position constancy for static objects during pursuit. This compensation is achieved in the process of sensorimotor integration of retinal and gaze signals: different retinal areas are integrated with different gaze signals to guarantee the stability of the visual world