Aspects of the Clausius-Shannon identity: emphasis on the components of transitive information in linear, branched and composite physical systems.
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Cybernetics↗
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Self-assembly and differentiation as models of computability.
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Cell Differentiation↗
Re-establishability in abstract biology.
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Cybernetics↗
Computer simulation of a self-preserving and learning organism.
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Computers↗
Studies in neurological structure. I. The geeral theory.
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Cybernetics↗
Insect visual homing strategies in a robot with analog processing.
The visual homing abilities of insects can be explained by the snapshot hypothesis. It asserts that an animal is guided to a previously visited location by comparing the current view with a snapshot taken at that location. The average landmark vector (ALV) model is a parsimonious navigation model based on the snapshot hypothesis. According to this model, the target location is unambiguously characterized by a signature vector extracted from the snapshot image. This article provides threefold support for the ALV model by synthetic modeling. First, it was shown that a mobile robot using the ALV model returns to the target location with only small position errors. Second, the behavior of the robot resembled the behavior of bees in some experiments. And third, the ALV model was implemented on the robot in analog hardware. This adds validity to the ALV model, since analog electronic circuits share a number of information-processing principles with biological nervous systems; the analog implementation therefore provides suggestions for how visual homing abilities might be implemented in the insect's brain.
Animals↗
Synergetic analysis of spatio-temporal EEG patterns: Alzheimer's disease.
A spatio-temporal analysis has been employed on EEG signals recorded in groups of patients with Alzheimer's disease (AD). The so-called Karhunen-Loeve analysis method was applied to four groups of subjects: 12 patients who were diagnosed as having severe AD, 8 mild AD patients, 10 vascular dementia patients, and 10 normal aged controls, to obtain the spatio-temporal eigenpatterns. The local difference of the global EEG pattern in mild AD patients from that of normal controls was expanded to the frontal regions in the case of severe AD. The analysis showed significant bilateral temporal functioning differences and inter-hemispheric connection difficulty, along with remarkable intra-hemispheric correlation in severe AD patients. Compared to the normal controls, severe AD patients' brains exhibit only weak local connections and correlations, resulting into limited harmonious inter-hemispheric information processing. The results from the spatio-temporal EEG study of AD patients can be considered to be due to a change in the relative activity of the brain corresponding to the pathologic variation in AD, and the results are in accordance with reported clinical studies.
Alzheimer Disease↗
Scaling behavior in beta-wave amplitude modulation and its relationship to alertness.
We performed an experimental study of beta waves occurring in human electroencephalographic signals obtained from six healthy subjects that were monitored during the performance of a task requiring attention to auditory signals. We use wavelet analysis to study whether the fluctuations in the modulation of the beta-wave amplitude related to an indirect measurement of alertness. We found that these fluctuations exhibit a power-law behavior. When the level of alertness dropped, the associated exponent was found to increase, reflecting the fact that long-range correlations grow rapidly within the system. We also studied the fluctuations of amplitude modulation for alpha and theta waves, for which we did not find a power-law behavior.
Acoustic Stimulation↗
The application of co-ordination dynamics to the analysis of discrete movements using table-tennis as a paradigm skill.
The purpose of this experiment was to explore the application of co-ordination dynamics to the analysis of discrete rather than cyclical movements. Subjects, standing in a fixed position, were required to return table-tennis balls delivered to different spatial locations in the direction of a fixed target. This was achieved in condition 1 by systematically scaling, from left to right and vice versa, the 'spatial location' of the ball-identified as a control parameter. In condition 2, the control condition, the spatial location was varied randomly over the same range. The changes between regimes of the stroke co-ordination pattern, defined at two different levels, (1) organisational--forehand or backhand drive. and (2) kinematic-the distance of the bat at ball-bat contact relative to the leading edge of the table, were identified as collective variables, the values of which changed spontaneously at the transition points exposed by the control parameter. The switch between regimes was shown to be dependent upon the direction of scaling, i.e. a hysteresis effect was identified in both conditions. These findings confirm that the conceptual and methodological frameworks of co-ordination dynamics can be applied, appropriately, to the analysis of discrete movements. Moreover, it would seem that control parameter values (spatial location of the ball) do not necessarily have to be scaled in a systematic way in order to produce the required effects.
Adult↗
Simulating mechanical consequences of voluntary movement upon whole-body equilibrium: the arm-raising paradigm revisited.
Voluntary arm-raising movement performed during the upright human stance position imposes a perturbation to an already unstable bipedal posture characterised by a high body centre of mass (CoM). Inertial forces due to arm acceleration and displacement of the CoM of the arm which alters the CoM position of the whole body represent the two sources of disequilibrium. A current model of postural control explains equilibrium maintenance through the action of anticipatory postural adjustments (APAs) that would offset any destabilising effect of the voluntary movement. The purpose of this paper was to quantify, using computer simulation, the postural perturbation due to arm raising movement. The model incorporated four links, with shoulder, hip, knee and ankle joints constrained by linear viscoelastic elements. The input of the model was a torque applied at the shoulder joint. The simulation described mechanical consequences of the arm-raising movement for different initial conditions. The variables tested were arm inertia, the presence or not of gravity field, the initial standing position and arm movement direction. Simulations showed that the mechanical effect of arm-raising movement was mainly local, that is to say at the level of trunk and lower limbs and produced a slight forward displacement of the CoM (1.5 mm). Backward arm-raising movement had the same effect on the CoM displacement as the forward arm-raising movement. When the mass of the arm was increased, trunk rotation increased producing a CoM displacement in the opposite direction when compared to arm movement performed without load. Postural disturbance was minimised for an initial standing posture with the CoM vertical projection corresponding to the ankle joint axis of rotation. When the model was reduced to two degrees of freedom (ankle and shoulder joints only) the postural perturbation due to arm-raising movement increased compared to the four-joints model. On the basis of these results the classical assumption that APAs stabilise the CoM is challenged.
Arm↗
Complex nonlinear dynamics of the Hodgkin-Huxley equations induced by time scale changes.
The Hodgkin-Huxley equations with a slight modification are investigated, in which the inactivation process (h) of sodium channels or the activation process of potassium channels (n) is slowed down. We show that the equations produce a variety of action potential waveforms ranging from a plateau potential, such as in heart muscle cells, to chaotic bursting firings. When h is slowed down--differently from the case of n variable being slow --chaotic bursting oscillations are observed for a wide range of parameter values although both variables cause a decrease in the membrane potential. The underlying nonlinear dynamics of various action potentials are analyzed using bifurcation theory and a so-called slow-fast decomposition analysis. It is shown that a simple topological property of the equilibrium curves of slow and fast subsystems is essential to the production of chaotic oscillations, and this is the cause of the large difference in global firing characteristics between the h-slow and n-slow cases.
Action Potentials↗
End-point constraints in aiming movements: effects of approach angle and speed.
The present study focuses on two trajectory-formation models of point-to-point aiming movements, viz., the minimum-jerk and the minimum torque-change model. To date, few studies on minimum-jerk and minimum torque-change trajectories have incorporated self- or externally imposed end-point constraints, such as the direction and velocity with which a target area is approached. To investigate which model accounts best for the effects on movement trajectories of such--in many circumstances - realistic end-point constraints, we adjusted both the minimum-jerk and the minimum torque-change model so that they could generate trajectories of which the final part has a specific direction and speed. The adjusted models yield realistic trajectories with a high curvature near movement completion. Comparison of simulated and measured movement trajectories show that pointing movements that are constrained with respect to final movement direction and speed can be described in terms of minimization of joint-torque changes.
Arm↗
An in silico central pattern generator: silicon oscillator, coupling, entrainment, and physical computation.
In biological systems, the task of computing a gait trajectory is shared between the biomechanical and nervous systems. We take the perspective that both of these seemingly different computations are examples of physical computation. Here we describe the progress that has been made toward building a minimal biped system that illustrates this idea. We embed a significant portion of the computation in physical devices, such as capacitors and transistors, to underline the potential power of emphasizing the understanding of physical computation. We describe results in the exploitation of physical computation by (1) using a passive knee to assist in dynamics computation, (2) using an oscillator to drive a monoped mechanism based on the passive knee, (3) using sensory entrainment to coordinate the mechanics with the neural oscillator, (4) coupling two such systems together mechanically at the hip and computationally via the resulting two oscillators to create a biped mechanism, and (5) demonstrating the resulting gait generation in the biped mechanism.
Bionics↗
Bifurcation properties of the average activity of interconnected neural populations.
The relevant scale for the study of the electrical activity of neural networks is a problem of mathematical and biological interest. From a continuous model of the cortex activity we derive a simple model of an interconnected pair of excitatory and inhibitory neural populations that describes the activity of a homogeneous network. Our model depends on three parameters that stand for the scale variability of the network. A bifurcation analysis reveals a great variety of patterns that arise from the interplay of excitatory and inhibitory populations provided by synaptic interactions. We emphasize the differences between the dynamical regimes when considering a moderate and a high inhibitory scale. We discuss the consequences on a propagating activity.
Animals↗
A novel model of motor learning capable of developing an optimal movement control law online from scratch.
A computational model of a learning system (LS) is described that acquires knowledge and skill necessary for optimal control of a multisegmental limb dynamics (controlled object or CO), starting from "knowing" only the dimensionality of the object's state space. It is based on an optimal control problem setup different from that of reinforcement learning. The LS solves the optimal control problem online while practicing the manipulation of CO. The system's functional architecture comprises several adaptive components, each of which incorporates a number of mapping functions approximated based on artificial neural nets. Besides the internal model of the CO's dynamics and adaptive controller that computes the control law, the LS includes a new type of internal model, the minimal cost (IM(mc)) of moving the controlled object between a pair of states. That internal model appears critical for the LS's capacity to develop an optimal movement trajectory. The IM(mc) interacts with the adaptive controller in a cooperative manner. The controller provides an initial approximation of an optimal control action, which is further optimized in real time based on the IM(mc). The IM(mc) in turn provides information for updating the controller. The LS's performance was tested on the task of center-out reaching to eight randomly selected targets with a 2DOF limb model. The LS reached an optimal level of performance in a few tens of trials. It also quickly adapted to movement perturbations produced by two different types of external force field. The results suggest that the proposed design of a self-optimized control system can serve as a basis for the modeling of motor learning that includes the formation and adaptive modification of the plan of a goal-directed movement.
Adaptation, Physiological↗
Head tilt-translation combinations distinguished at the level of neurons.
Angular and linear accelerations of the head occur throughout everyday life, whether from external forces such as in a vehicle or from volitional head movements. The relative timing of the angular and linear components of motion differs depending on the movement. The inner ear detects the angular and linear components with its semicircular canals and otolith organs, respectively, and secondary neurons in the vestibular nuclei receive input from these vestibular organs. Many secondary neurons receive both angular and linear input. Linear information alone does not distinguish between translational linear acceleration and angular tilt, with its gravity-induced change in the linear acceleration vector. Instead, motions are thought to be distinguished by use of both angular and linear information. However, for combined motions, composed of angular tilt and linear translation, the infinite range of possible relative timing of the angular and linear components gives an infinite set of motions among which to distinguish the various types of movement. The present research focuses on motions consisting of angular tilt and horizontal translation, both sinusoidal, where the relative timing, i.e. phase, of the tilt and translation can take any value in the range -180 degrees to 180 degrees . The results show how hypothetical neurons receiving convergent input can distinguish tilt from translation, and that each of these neurons has a preferred combined motion, to which the neuron responds maximally. Also shown are the values of angular and linear response amplitudes and phases that can cause a neuron to be tilt-only or translation-only. Such neurons turn out to be sufficient for distinguishing between combined motions, with all of the possible relative angular-linear phases. Combinations of other neurons, as well, are shown to distinguish motions. Relative response phases and in-phase firing-rate modulation are the key to identifying specific motions from within this infinite set of combined motions.
Cybernetics↗
Bipedal locomotion: toward unified concepts in robotics and neuroscience.
This review is the result of a joint reflection carried out by researchers in the fields of robotics and automatic control on the one hand and neuroscience on the other, both trying to answer the same question: what are the functional bases of bipedal locomotion and how can they be controlled? The originality of this work is to synthesize the two approaches in order to take advantage of the knowledge concerning the adaptability and reactivity performances of humans and of the rich tools and formal concepts available in biped robotics. Indeed, we claim that the theoretical framework of robotics can enhance our understanding of human postural control by formally expressing the experimental concepts used in neuroscience. Conversely, biological knowledge of human posture and gait can inspire biped robot design and control. Therefore, both neuroscientists and roboticists should find useful information in this paper.
Cybernetics↗