On Neuromechanical Approaches for the Study of Biological Grasp and Manipulation

Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas

Excitatory postsynaptic potentials in rat neocortical neurons in vitro. III. Effects of a quinoxalinedione non-NMDA receptor antagonist

1. Intracellular microelectrodes were used to obtain recordings from neurons in layer II/III of rat frontal cortex. A bipolar electrode positioned in layer IV of the neocortex was used to evoke postsynaptic potentials. Graded series of stimulation were employed to selectively activate different classes of postsynaptic responses. The sensitivity of postsynaptic potentials and iontophoretically applied neurotransmitters to the non-N-methyl-D-asparate (NMDA) antagonist 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX) was examined. 2. As reported previously, low-intensity electrical stimulation of cortical layer IV evoked short-latency early excitatory postsynaptic potentials (eEPSPs) in layer II/III neurons. CNQX reversibly antagonized eEPSPs in a dose-dependent manner. Stimulation at intensities just subthreshold for activation of inhibitory postsynaptic potentials (IPSPs) produced long-latency (10 to 40-ms) EPSPs (late EPSPs or 1EPSPs). CNQX was effective in blocking 1EPSPs. 3. With the use of stimulus intensities at or just below threshold for evoking an action potential, complex synaptic potentials consisting of EPSP-IPSP sequences were observed. Both early, Cl(-)-dependent and late, K(+)-dependent IPSPs were reduced by CNQX. This effect was reversible on washing. This disinhibition could lead to enhanced excitability in the presence of CNQX. 4. Iontophoretic application of quisqualate produced a membrane depolarization with superimposed action potentials, whereas NMDA depolarized the membrane potential and evoked bursts of action potentials. At concentrations up to 5 microM, CNQX selectively antagonized quisqualate responses. NMDA responses were reduced by 10 microM CNQX. D-Serine (0.5-2 mM), an agonist at the glycine regulatory site on the NMDA receptor, reversed the CNQX depression of NMDA responses

Reach-To-Grasp Movements: A Multimodal Techniques Study

The aim of the present study was to investigate the correlation between corticospinal activity, kinematics, and electromyography (EMG) associated with the execution of precision and whole-hand grasps (WHGs). To this end, motor-evoked potentials (MEPs) induced by transcranial magnetic stimulation (TMS), EMG, and 3-D motion capture data have been simultaneously recorded during the planning and the execution of prehensile actions toward either a small or a large object. Differences in the considered measures were expected to distinguish between the two types of grasping actions both in terms of action preparation and execution. The results indicate that the index finger (FDI) and the little finger (ADM) muscles showed different activation patterns during grasping execution, but only the FDI appeared to distinguish between the two types of actions during motor preparation. Kinematics analysis showed that precision grips differed from WHGs in terms of displayed fingers distance when shaping before object\u2019s contact, and in terms of timing and velocity patterns. Moreover, significant correlations suggest a relationship between the muscular activation and the temporal aspects concerned with the index finger\u2019s extension during whole-hand actions. Overall, the present data seem to suggest a crucial role played by index finger as an early \u201cmarker\u201d of differential motor preparation for different types of grasps and as a \u201cnavigator\u201d in guiding whole-hand prehensile actions. Aside from the novelty of the methodological approach characterizing the present study, the data provide new insights regarding the level of crosstalk among different levels concerned with the neuro-behavioral organization of reach-to-grasp movements

Semantic distillation: a method for clustering objects by their contextual specificity

Techniques for data-mining, latent semantic analysis, contextual search of databases, etc. have long ago been developed by computer scientists working on information retrieval (IR). Experimental scientists, from all disciplines, having to analyse large collections of raw experimental data (astronomical, physical, biological, etc.) have developed powerful methods for their statistical analysis and for clustering, categorising, and classifying objects. Finally, physicists have developed a theory of quantum measurement, unifying the logical, algebraic, and probabilistic aspects of queries into a single formalism. The purpose of this paper is twofold: first to show that when formulated at an abstract level, problems from IR, from statistical data analysis, and from physical measurement theories are very similar and hence can profitably be cross-fertilised, and, secondly, to propose a novel method of fuzzy hierarchical clustering, termed \textit{semantic distillation} -- strongly inspired from the theory of quantum measurement --, we developed to analyse raw data coming from various types of experiments on DNA arrays. We illustrate the method by analysing DNA arrays experiments and clustering the genes of the array according to their specificity.Comment: Accepted for publication in Studies in Computational Intelligence, Springer-Verla

Are joint torque models limited by an assumption of monoarticularity?

This study determines whether maximal voluntary ankle plantar flexor torque could be more accurately represented using a torque generator that is a function of both knee and ankle kinematics. Iso velocity and isometric ankle plantar flexor torques were measured on a single participant for knee joint angles of 111° to 169° (approximately full extension) using a Contrex M J dynamometer. Maximal voluntary torque was represented by a 19-parameter two-joint function of ankle and knee joint angles and angular velocities with the parameters determined by minimizing a weighted root mean square difference between measured torques and the two-joint function. The weighted root mean square difference between the two-joint function and the measured torques was 10 N-m or 3% of maximum torque. The two-joint function was a more accurate representation of maximal voluntary ankle plantar flexor torques than an existing single-joint function where differences of 19% of maximum torque were found. It is concluded that when the knee is flexed by more than 40°, a two-joint representation is necessary

Anatomical information science

The Foundational Model of Anatomy (FMA) is a map of the human body. Like maps of other sorts – including the map-like representations we find in familiar anatomical atlases – it is a representation of a certain portion of spatial reality as it exists at a certain (idealized) instant of time. But unlike other maps, the FMA comes in the form of a sophisticated ontology of its objectdomain, comprising some 1.5 million statements of anatomical relations among some 70,000 anatomical kinds. It is further distinguished from other maps in that it represents not some specific portion of spatial reality (say: Leeds in 1996), but rather the generalized or idealized spatial reality associated with a generalized or idealized human being at some generalized or idealized instant of time. It will be our concern in what follows to outline the approach to ontology that is represented by the FMA and to argue that it can serve as the basis for a new type of anatomical information science. We also draw some implications for our understanding of spatial reasoning and spatial ontologies in general

A Model of Movement Coordinates in Motor Cortex: Posture-Dependent Changes in the Gain and Direction of Single Cell Tuning Curves

Central to the problem of elucidating the cortical mechanisms that mediate movement behavior is an investigation of the coordinate systems by which movement variables are encoded in the firing rates of individual motor cortical neurons. In the last decade, neurophysiologists have probed how the preferred direction of an individual motor cortical cell (as determined by a center-out task) will change with posture because such changes are useful for inferring underlying cordinates. However, while the importance of shifts in preferred direction is well-known and widely accepted, posture-dependent changes in the depth of modulation of a cell's tuning curve, i.e. gain changes, have not been similarly identified as a means of coordinate inference. This paper develops a vector field framework which, by viewing the preferred direction and the gain of a cell's tuning curve as dual components of a unitary response vector, can compute how each aspect of cell response covaries with posture as a function of the coordinate system in which a given cell is hypothesized to encode its movement information. This integrated approach leads to a model of motor cortical cell activity that codifies the following four observations: 1) cell activity correlates with hand movement direction, 2) cell activity correlates with hand movement speed, 3) preferred directions vary with posture, and 4) the modulation depth of tuning curves varies with posture. Finally, the model suggests general methods for testing coordinate hypotheses at the single cell level and example protocols arc simulated for three possible coordinate systems: Cartesian spatial, shoulder-centered, and joint angle.Defense Advanced Research Projects Agency (N00014-92-J-4015); Defense Advanced Research Projects Agency and the Office of Naval Research (N00014-95-1-0409); National Science Foundation (IRI-90-00530, IRI-97-20333); Office of Naval Research (N00014-91-J-4100, N00014-92-J-1309, N00014-94-l-0940, N00014-95-1-0657)

Phylogenetic Analysis of Cell Types using Histone Modifications

In cell differentiation, a cell of a less specialized type becomes one of a more specialized type, even though all cells have the same genome. Transcription factors and epigenetic marks like histone modifications can play a significant role in the differentiation process. In this paper, we present a simple analysis of cell types and differentiation paths using phylogenetic inference based on ChIP-Seq histone modification data. We propose new data representation techniques and new distance measures for ChIP-Seq data and use these together with standard phylogenetic inference methods to build biologically meaningful trees that indicate how diverse types of cells are related. We demonstrate our approach on H3K4me3 and H3K27me3 data for 37 and 13 types of cells respectively, using the dataset to explore various issues surrounding replicate data, variability between cells of the same type, and robustness. The promising results we obtain point the way to a new approach to the study of cell differentiation.Comment: Peer-reviewed and presented as part of the 13th Workshop on Algorithms in Bioinformatics (WABI2013