Learning to grasp and extract affordances: the Integrated Learning of Grasps and Affordances (ILGA) model

The activity of certain parietal neurons has been interpreted as encoding affordances (directly perceivable opportunities) for grasping. Separate computational models have been developed for infant grasp learning and affordance learning, but no single model has yet combined these processes in a neurobiologically plausible way. We present the Integrated Learning of Grasps and Affordances (ILGA) model that simultaneously learns grasp affordances from visual object features and motor parameters for planning grasps using trial-and-error reinforcement learning. As in the Infant Learning to Grasp Model, we model a stage of infant development prior to the onset of sophisticated visual processing of hand–object relations, but we assume that certain premotor neurons activate neural populations in primary motor cortex that synergistically control different combinations of fingers. The ILGA model is able to extract affordance representations from visual object features, learn motor parameters for generating stable grasps, and generalize its learned representations to novel objects

Recognizing Speech in a Novel Accent: The Motor Theory of Speech Perception Reframed

The motor theory of speech perception holds that we perceive the speech of another in terms of a motor representation of that speech. However, when we have learned to recognize a foreign accent, it seems plausible that recognition of a word rarely involves reconstruction of the speech gestures of the speaker rather than the listener. To better assess the motor theory and this observation, we proceed in three stages. Part 1 places the motor theory of speech perception in a larger framework based on our earlier models of the adaptive formation of mirror neurons for grasping, and for viewing extensions of that mirror system as part of a larger system for neuro-linguistic processing, augmented by the present consideration of recognizing speech in a novel accent. Part 2 then offers a novel computational model of how a listener comes to understand the speech of someone speaking the listener's native language with a foreign accent. The core tenet of the model is that the listener uses hypotheses about the word the speaker is currently uttering to update probabilities linking the sound produced by the speaker to phonemes in the native language repertoire of the listener. This, on average, improves the recognition of later words. This model is neutral regarding the nature of the representations it uses (motor vs. auditory). It serve as a reference point for the discussion in Part 3, which proposes a dual-stream neuro-linguistic architecture to revisits claims for and against the motor theory of speech perception and the relevance of mirror neurons, and extracts some implications for the reframing of the motor theory

A Computation in a Cellular Automaton Collider Rule 110

A cellular automaton collider is a finite state machine build of rings of one-dimensional cellular automata. We show how a computation can be performed on the collider by exploiting interactions between gliders (particles, localisations). The constructions proposed are based on universality of elementary cellular automaton rule 110, cyclic tag systems, supercolliders, and computing on rings.Comment: 39 pages, 32 figures, 3 table

Learning automata with side-effects

Automata learning has been successfully applied in the verification of hardware and software. The size of the automaton model learned is a bottleneck for scalability, and hence optimizations that enable learning of compact representations are important. This paper exploits monads, both as a mathematical structure and a programming construct, to design and prove correct a wide class of such optimizations. Monads enable the development of a new learning algorithm and correctness proofs, building upon a general framework for automata learning based on category theory. The new algorithm is parametric on a monad, which provides a rich algebraic structure to capture non-determinism and other side-effects. We show that this allows us to uniformly capture existing algorithms, develop new ones, and add optimizations

Molecular basis of structure and function of the microvillus membrane of intestinal epithelial cells

Correlation of molecular structure with biochemical functions of the plasma membrane of the microvilli of intestinal epithelial cells has been investigated by biochemical and electron microscopic procedures. Repeating particles, measuring approximately 60 &#197;in diameter, were found on the surface of the microvilli membrane which had been isolated or purified from rabbit intestinal epithelial cells and negatively stained with phosphotungstic acid. These particles were proved to be inherent components of the microvillus membrane, attached to the outer surface of its trilaminar structure, and were designated as the elementary particles of the microvilli of intestinal epithelial cells. Biochemical and electron microscopic identification of these elementary particles has been carried out by isolation of the elementary particles with papain from the isolated microvillus membrane, followed by purification of the particles by chromatographies on DEAE-cellulose and Sephadex columns. The partially purified particles containing invertase and leucine aminopeptidase are similar in size and structure to those of the elementary particles in the microvillus membrane. Evidence indicates that each of the elementary particles coincide with or include an enzyme molecule such as disaccharidase or peptidase, which carry out the terminal hydrolytic digestion of carbohydrates and proteins, respectively, on the surface of the microvillus membrane. Magnesium ionactivated adenosine triphosphatase and alkaline phosphatase cannot be solubilized with papain but remains in the smooth-surface membrane after the elementary particles have been removed. Cytochemical electron microscopic observation revealed that the active site of magnesium ion-activated adenosine triphosphatase is localized predominantly in the inner surface of the trilaminar structure of the microvillus membrane.</p

Symmetry structure in discrete models of biochemical systems : natural subsystems and the weak control hierarchy in a new model of computation driven by interactions

© 2015 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.Interaction Computing (IC) is inspired by the observation that cell metabolic/regulatory systems construct order dynamically, through constrained interactions between their components and based on a wide range of possible inputs and environmental conditions. The goals of this work are (1) to identify and understand mathematically the natural subsystems and hierarchical relations in natural systems enabling this, and (2) to use the resulting insights to define a new model of computation based on interactions that is useful for both biology and computation. The dynamical characteristics of the cellular pathways studied in Systems Biology relate, mathematically, to the computational characteristics of automata derived from them, and their internal symmetry structures to computational power. Finite discrete automata models of biological systems such as the lac operon, Krebs cycle, and p53-mdm2 genetic regulation constructed from Systems Biology models have canonically associated algebraic structures { transformation semigroups. These contain permutation groups (local substructures exhibiting symmetry) that correspond to "pools of reversibility". These natural subsystems are related to one another in a hierarchical manner by the notion of "weak control ". We present natural subsystems arising from several biological examples and their weak control hierarchies in detail. Finite simple non-abelian groups (SNAGs) are found in biological examples and can be harnessed to realize nitary universal computation. This allows ensembles of cells to achieve any desired finitary computational transformation, depending on external inputs, via suitably constrained interactions. Based on this, interaction machines that grow and change their structure recursively are introduced and applied, providing a natural model of computation driven by interactions.Peer reviewe

MIRO: A robot “Mammal” with a biomimetic brain-based control system

We describe the design of a novel commercial biomimetic brain-based robot, MIRO, developed as a prototype robot companion. The MIRO robot is animal-like in several aspects of its appearance, however, it is also biomimetic in a more significant way, in that its control architecture mimics some of the key principles underlying the design of the mammalian brain as revealed by neuroscience. Specifically, MIRO builds on decades of previous work in developing robots with brain-based control systems using a layered control architecture alongside centralized mechanisms for integration and action selection. MIRO’s control system operates across three core processors, P1-P3, that mimic aspects of spinal cord, brainstem, and forebrain functionality respectively. Whilst designed as a versatile prototype for next generation companion robots, MIRO also provides developers and researchers with a new platform for investigating the potential advantages of brain-based control

Observation of Static Pictures of Dynamic Actions Enhances the Activity of Movement-Related Brain Areas

Physiological studies of perfectly still observers have shown interesting correlations between increasing effortfulness of observed actions and increases in heart and respiration rates. Not much is known about the cortical response induced by observing effortful actions. The aim of this study was to investigate the time course and neural correlates of perception of implied motion, by presenting 260 pictures of human actions differing in degrees of dynamism and muscular exertion. ERPs were recorded from 128 sites in young male and female adults engaged in a secondary perceptual task.Our results indicate that even when the stimulus shows no explicit motion, observation of static photographs of human actions with implied motion produces a clear increase in cortical activation, manifest in a long-lasting positivity (LP) between 350–600 ms that is much greater to dynamic than less dynamic actions, especially in men. A swLORETA linear inverse solution computed on the dynamic-minus-static difference wave in the time window 380–430 ms showed that a series of regions was activated, including the right V5/MT, left EBA, left STS (BA38), left premotor (BA6) and motor (BA4) areas, cingulate and IF cortex.Overall, the data suggest that corresponding mirror neurons respond more strongly to implied dynamic than to less dynamic actions. The sex difference might be partially cultural and reflect a preference of young adult males for highly dynamic actions depicting intense muscular activity, or a sporty context

Joint angle variability and co-variation in a reaching with a rod task

The problem at the heart of motor control is how the myriad units of the neuromotor system are coordinated to perform goal-directed movements. Although for long these numerous degrees of freedom (DOFs) were considered redundant, recent views emphasize more that the DOFs should be considered abundant, allowing flexible performance. We studied how variability in arm joints was employed to stabilize the displaced end-effector in tool use to examine how the neuromotor system flexibly exploits DOFs in the upper extremity. Participants made pointing movements with the index finger and with the index finger extended by rods of 10, 20, and 30 cm. Using the uncontrolled manifold (UCM) method, the total joint angle variance was decomposed into two parts, the joint angle variance that did not affect the position of the end-effector (VUCM) and the variance that results in a deviation of the position of the end-effector from its mean (VORT). Analyses showed that some angles depended on length of the rod in use. For all rod lengths, VUCM was larger than VORT, and this did not differ over rod lengths, demonstrating that the arm was organized into a synergy. Finally, the variation in the joint angles in the arm as well as the degree of co-variation between these angles did not differ for the rod’s tip and the hand. We concluded that synergies are formed in the arm during reaching with an extended end-effector and those synergies stabilize different parts of the arm+rod system equally