Grasp Analysis Tools for Synergistic Underactuated Robotic Hands

Despite being a classical topic in robotics, the research on dexterous robotic hands still stirs a lively research activity. The current interest is especially attracted by underactuated robotic hands where a high number of degrees of freedom (DoFs), and a relatively low number of degrees of actuation co-exist. The correlation between the DoFs obtained through a wise distribution of actuators is aimed at simplifying the control with a minimal loss of dexterity. In this sense, the application of bio-inspired principles is bringing research toward a more conscious design. This work proposes new, general approaches for the analysis of grasps with synergistic underactuated robotic hands.After a review of the quasi-static equations describing the system, where contact preload is also considered, two different approaches to the analysis are presented. The first one is based on a systematic combination of the equations. The independent and the dependent variables are defined, and cause-effect relationships between them are found. In addition, remarkable properties of the grasp, as the subspace of controllable internal force and the grasp compliance, are worked out in symbolic form. Then, some relevant kinds of tasks, such as pure squeeze, spurious squeeze and kinematic grasp displacements, are defined, in terms of nullity or non-nullity of proper variables. The second method of analysis shows how to discover the feasibility of the pre-defined tasks, operating a systematic decomposition of the solution space of the system. As a result, the inputs to be given to the hand, in order to achieve the desired system displacements, are found. The study of the feasible variations is carried out arriving at the discovery of all the combinations of nullity and/or non-nullity variables which are allowed by the equations describing the system. Numerical results are presented both for precision and power grasps, finding forces and displacements that the hand can impose on the object, and showing which properties are preserved after the introduction of a synergistic underactuation mechanism

T-wave Inversion through Inhomogeneous Voltage Diffusion within the FK3V Cardiac Model

The heart beats due to the synchronized contraction of cardiomyocytes triggered by a periodic sequence of electrical signals called action potentials, which originate in the sinoatrial node and spread through the heart's electrical system. A large body of work is devoted to modeling the propagation of the action potential and to reproducing reliably its shape and duration. Connection of computational modeling of cells to macroscopic phenomenological curves such as the electrocardiogram has been also intense, due to its clinical importancce in analyzing cardiovascular diseases. In this work we simulate the dynamics of action potential propagation using the three-variable Fenton-Karma model that can account for both normal and damaged cells through spatially inhomogeneous voltage diffusion coefficient. We monitor the action potential propagation in the cardiac tissue and calculate the pseudo-electrocardiogram that reproduces the R and T waves. The R wave amplitude varies according to a double exponential law as a function of the (spatially homogeneous, for an isotropic tissue) diffusion coefficient. The addition of spatial inhomogeneity in the diffusion coefficient by means of a defected region representing damaged cardiac cells, may result in T-wave inversion in the calculated pseudo-electrocardiogram. The transition from positive to negative polarity of the T-wave is analyzed as a function of the length and the depth of the defected region.Comment: 12 pages, figures, 39 reference

Multisensory causal inference in the brain

At any given moment, our brain processes multiple inputs from its different sensory modalities (vision, hearing, touch, etc.). In deciphering this array of sensory information, the brain has to solve two problems: (1) which of the inputs originate from the same object and should be integrated and (2) for the sensations originating from the same object, how best to integrate them. Recent behavioural studies suggest that the human brain solves these problems using optimal probabilistic inference, known as Bayesian causal inference. However, how and where the underlying computations are carried out in the brain have remained unknown. By combining neuroimaging-based decoding techniques and computational modelling of behavioural data, a new study now sheds light on how multisensory causal inference maps onto specific brain areas. The results suggest that the complexity of neural computations increases along the visual hierarchy and link specific components of the causal inference process with specific visual and parietal regions

Peaks and Troughs of Three-Dimensional Vestibulo-ocular Reflex in Humans

The three-dimensional vestibulo-ocular reflex (3D VOR) ideally generates compensatory ocular rotations not only with a magnitude equal and opposite to the head rotation but also about an axis that is collinear with the head rotation axis. Vestibulo-ocular responses only partially fulfill this ideal behavior. Because animal studies have shown that vestibular stimulation about particular axes may lead to suboptimal compensatory responses, we investigated in healthy subjects the peaks and troughs in 3D VOR stabilization in terms of gain and alignment of the 3D vestibulo-ocular response. Six healthy upright sitting subjects underwent whole body small amplitude sinusoidal and constant acceleration transients delivered by a six-degree-of-freedom motion platform. Subjects were oscillated about the vertical axis and about axes in the horizontal plane varying between roll and pitch at increments of 22.5° in azimuth. Transients were delivered in yaw, roll, and pitch and in the vertical canal planes. Eye movements were recorded in with 3D search coils. Eye coil signals were converted to rotation vectors, from which we calculated gain and misalignment. During horizontal axis stimulation, systematic deviations were found. In the light, misalignment of the 3D VOR had a maximum misalignment at about 45°. These deviations in misalignment can be explained by vector summation of the eye rotation components with a low gain for torsion and high gain for vertical. In the dark and in response to transients, gain of all components had lower values. Misalignment in darkness and for transients had different peaks and troughs than in the light: its minimum was during pitch axis stimulation and its maximum during roll axis stimulation. We show that the relatively large misalignment for roll in darkness is due to a horizontal eye movement component that is only present in darkness. In combination with the relatively low torsion gain, this horizontal component has a relative large effect on the alignment of the eye rotation axis with respect to the head rotation axis

Non-linear stimulus-response behavior of the human stance control system is predicted by optimization of a system with sensory and motor noise

We developed a theory of human stance control that predicted (1) how subjects re-weight their utilization of proprioceptive and graviceptive orientation information in experiments where eyes closed stance was perturbed by surface-tilt stimuli with different amplitudes, (2) the experimentally observed increase in body sway variability (i.e. the “remnant” body sway that could not be attributed to the stimulus) with increasing surface-tilt amplitude, (3) neural controller feedback gains that determine the amount of corrective torque generated in relation to sensory cues signaling body orientation, and (4) the magnitude and structure of spontaneous body sway. Responses to surface-tilt perturbations with different amplitudes were interpreted using a feedback control model to determine control parameters and changes in these parameters with stimulus amplitude. Different combinations of internal sensory and/or motor noise sources were added to the model to identify the properties of noise sources that were able to account for the experimental remnant sway characteristics. Various behavioral criteria were investigated to determine if optimization of these criteria could predict the identified model parameters and amplitude-dependent parameter changes. Robust findings were that remnant sway characteristics were best predicted by models that included both sensory and motor noise, the graviceptive noise magnitude was about ten times larger than the proprioceptive noise, and noise sources with signal-dependent properties provided better explanations of remnant sway. Overall results indicate that humans dynamically weight sensory system contributions to stance control and tune their corrective responses to minimize the energetic effects of sensory noise and external stimuli

Evidence for cognitive vestibular integration impairment in idiopathic scoliosis patients

<p>Abstract</p> <p>Background</p> <p>Adolescent idiopathic scoliosis is characterized by a three-dimensional deviation of the vertebral column and its etiopathogenesis is unknown. Various factors cause idiopathic scoliosis, and among these a prominent role has been attributed to the vestibular system. While the deficits in sensorimotor transformations have been documented in idiopathic scoliosis patients, little attention has been devoted to their capacity to integrate vestibular information for cognitive processing for space perception. Seated idiopathic scoliosis patients and control subjects experienced rotations of different directions and amplitudes in the dark and produced saccades that would reproduce their perceived spatial characteristics of the rotations (vestibular condition). We also controlled for possible alteration of the oculomotor and vestibular systems by measuring the subject's accuracy in producing saccades towards memorized peripheral targets in absence of body rotation and the gain of their vestibulo-ocular reflex.</p> <p>Results</p> <p>Compared to healthy controls, the idiopathic scoliosis patients underestimated the amplitude of their rotations. Moreover, the results revealed that idiopathic scoliosis patients produced accurate saccades to memorized peripheral targets in absence of body rotation and that their vestibulo-ocular reflex gain did not differ from that of control participants.</p> <p>Conclusion</p> <p>Overall, results of the present study demonstrate that idiopathic scoliosis patients have an alteration in cognitive integration of vestibular signals. It is possible that severe spine deformity developed partly due to impaired vestibular information travelling from the cerebellum to the vestibular cortical network or alteration in the cortical mechanisms processing the vestibular signals.</p

Standardized and reproducible measurement of decision-making in mice

Progress in science requires standardized assays whose results can be readily shared, compared, and reproduced across laboratories. Reproducibility, however, has been a concern in neuroscience, particularly for measurements of mouse behavior. Here we show that a standardized task to probe decision-making in mice produces reproducible results across multiple laboratories. We designed a task for head-fixed mice that combines established assays of perceptual and value-based decision making, and we standardized training protocol and experimental hardware, software, and procedures. We trained 140 mice across seven laboratories in three countries, and we collected 5 million mouse choices into a publicly available database. Learning speed was variable across mice and laboratories, but once training was complete there were no significant differences in behavior across laboratories. Mice in different laboratories adopted similar reliance on visual stimuli, on past successes and failures, and on estimates of stimulus prior probability to guide their choices. These results reveal that a complex mouse behavior can be successfully reproduced across multiple laboratories. They establish a standard for reproducible rodent behavior, and provide an unprecedented dataset and open-access tools to study decision-making in mice. More generally, they indicate a path towards achieving reproducibility in neuroscience through collaborative open-science approaches

Local Field Potential Modeling Predicts Dense Activation in Cerebellar Granule Cells Clusters under LTP and LTD Control

Local field-potentials (LFPs) are generated by neuronal ensembles and contain information about the activity of single neurons. Here, the LFPs of the cerebellar granular layer and their changes during long-term synaptic plasticity (LTP and LTD) were recorded in response to punctate facial stimulation in the rat in vivo. The LFP comprised a trigeminal (T) and a cortical (C) wave. T and C, which derived from independent granule cell clusters, co-varied during LTP and LTD. To extract information about the underlying cellular activities, the LFP was reconstructed using a repetitive convolution (ReConv) of the extracellular potential generated by a detailed multicompartmental model of the granule cell. The mossy fiber input patterns were determined using a Blind Source Separation (BSS) algorithm. The major component of the LFP was generated by the granule cell spike Na+ current, which caused a powerful sink in the axon initial segment with the source located in the soma and dendrites. Reproducing the LFP changes observed during LTP and LTD required modifications in both release probability and intrinsic excitability at the mossy fiber-granule cells relay. Synaptic plasticity and Golgi cell feed-forward inhibition proved critical for controlling the percentage of active granule cells, which was 11% in standard conditions but ranged from 3% during LTD to 21% during LTP and raised over 50% when inhibition was reduced. The emerging picture is that of independent (but neighboring) trigeminal and cortical channels, in which synaptic plasticity and feed-forward inhibition effectively regulate the number of discharging granule cells and emitted spikes generating “dense” activity clusters in the cerebellar granular layer

Acoustic Overexposure Increases the Expression of VGLUT-2 Mediated Projections from the Lateral Vestibular Nucleus to the Dorsal Cochlear Nucleus

The dorsal cochlear nucleus (DCN) is a first relay of the central auditory system as well as a site for integration of multimodal information. Vesicular glutamate transporters VGLUT-1 and VGLUT-2 selectively package glutamate into synaptic vesicles and are found to have different patterns of organization in the DCN. Whereas auditory nerve fibers predominantly co-label with VGLUT-1, somatosensory inputs predominantly co-label with VGLUT-2. Here, we used retrograde and anterograde transport of fluorescent conjugated dextran amine (DA) to demonstrate that the lateral vestibular nucleus (LVN) exhibits ipsilateral projections to both fusiform and deep layers of the rat DCN. Stimulating the LVN induced glutamatergic synaptic currents in fusiform cells and granule cell interneurones. We combined the dextran amine neuronal tracing method with immunohistochemistry and showed that labeled projections from the LVN are co-labeled with VGLUT-2 by contrast to VGLUT-1. Wistar rats were exposed to a loud single tone (15 kHz, 110 dB SPL) for 6 hours. Five days after acoustic overexposure, the level of expression of VGLUT-1 in the DCN was decreased whereas the level of expression of VGLUT-2 in the DCN was increased including terminals originating from the LVN. VGLUT-2 mediated projections from the LVN to the DCN are likely to play a role in the head position in response to sound. Amplification of VGLUT-2 expression after acoustic overexposure could be a compensatory mechanism from vestibular inputs in response to hearing loss and to a decrease of VGLUT-1 expression from auditory nerve fibers

Contribution of Cerebellar Sensorimotor Adaptation to Hippocampal Spatial Memory

Complementing its primary role in motor control, cerebellar learning has also a bottom-up influence on cognitive functions, where high-level representations build up from elementary sensorimotor memories. In this paper we examine the cerebellar contribution to both procedural and declarative components of spatial cognition. To do so, we model a functional interplay between the cerebellum and the hippocampal formation during goal-oriented navigation. We reinterpret and complete existing genetic behavioural observations by means of quantitative accounts that cross-link synaptic plasticity mechanisms, single cell and population coding properties, and behavioural responses. In contrast to earlier hypotheses positing only a purely procedural impact of cerebellar adaptation deficits, our results suggest a cerebellar involvement in high-level aspects of behaviour. In particular, we propose that cerebellar learning mechanisms may influence hippocampal place fields, by contributing to the path integration process. Our simulations predict differences in place-cell discharge properties between normal mice and L7-PKCI mutant mice lacking long-term depression at cerebellar parallel fibre-Purkinje cell synapses. On the behavioural level, these results suggest that, by influencing the accuracy of hippocampal spatial codes, cerebellar deficits may impact the exploration-exploitation balance during spatial navigation