A synergetic theory of environmentally-specified and learned patterns of movement coordination

By combining neuropharmacology and electrophysiology, we tried to determine whether the main neuronal mechanism responsible for direction-selective motion detection in the fly is based on an excitatory or an inhibitory synaptic interaction. By blocking inhibitory interactions with picrotoxinin, an antagonist of the inhibitory neurotransmitter GABA, we could abolish most of the directional selectivity of a large-field movement-sensitive neuron (H1-cell) in the lobula plate of the blowfly Calliphora erythrocephala. These modifications are similar to changes observed in the optomotor response of the fruitfly Drosophila melanogaster after application of picrotoxinin (Bülthoff and Bülthoff 1987a, b). Assuming a simplified logical model, these results are compatible with inhibitory synaptic interactions at the level of the elementary movement detectors. The picrotoxinin-induced changes in direction selectivity are not due to modifications of the peripheral visual processing in the retina and lamina. This was shown by simultaneous recordings of the electroretinogram and the H1-cell. The latencies between drug injections into various parts of the brain and their first effects on the H1-cell suggest that the inhibitory mechanism for motion detection is located in the medulla rather than in the lobula plate.     

A synergetic theory of environmentally-specified and learned patterns of movement coordination

Rhythmic movement patterns have served as a model case for developing a synergetic theory of biological coordination. In part I of this work we extended the approach to environmentally-specified and learned movement patterns on the level of the collective variable relative phase. Here we show that an identical strategy may be applied to the same problem at the level of the component oscillators. Coordinative patterns and their dynamics are derived from the coupled component dynamics and their interaction with the environment. Thus, behavioral patterns are shown to arise in a purely self-organized fashion. New directions for further research (e.g. dynamics of action-perception systems) follow from the oscillator theory. Finally the relationship between our approach and other kinds of analyses of temporal order (e.g. phase resetting) is addressed.     

Learning and recall in a dynamic theory of coordination patterns

A dynamic theory of learning and recall of coordination patterns is developed in the context of relative timing skills. Characterizing the coordination patterns in such skills by the collective variable, relative phase, we choose a model system in which the intrinsic pattern dynamics as well as the influence of environmental and memorized information are well understood from previous experimental and theoretical work. To describe learning we endow memorized information with dynamics which is determined by a phenomenological strategy. Similarly, additional degrees of freedom must be introduced to understand recall. As such recall variables we choose the relative strengths with which each memorized pattern acts on the pattern dynamics and model their dynamics phenomenologically. The resulting dynamical system that resembles models used in pattern recognition theory is shown to adequately describe the learning and recall processes. Moreover, due to the operational character of the theory, several predictions emerge that are open to experimental test. In particular, we show under which conditions phase transitions occur in the dynamics of the coordination patterns during learning and during recall. Considering different time scales and their relations we demonstrate how these phase transitions can be identified and observed. Other predictions include the influence of the intrinsic pattern dynamics on the recall process and the existence of history and hysteresis effects in recall. We discuss different forms of forgetting and differentiation of memorized information. The results show how a new theoretical view of learning and recall as change of behavioral dynamics can lead to a different understanding of these processes by providing testable predictions.     

A model of coordination of sperm flagella movement

The periodicity of bulls and humans' spermatozoa motion is investigated. The period of their motion is divisible by 24 and 15 turns of spermatozoa heads respectively. The interrelation of the observed periodicity with the ultrastructure of gamete tails is pre-supposed. A model of mitochondrial coordination of sperm flagella movement is proposed.     

A mechanistic theory of personality‐dependent movement behaviour based on dynamic energy budgets

Consistent between‐individual differences in movement are widely recognised across taxa. In addition, foraging plasticity at the within‐individual level suggests a behavioural dependency on the internal energy demand. Because behaviour co‐varies with fast‐slow life history (LH) strategies in an adaptive context, as theoretically predicted by the pace‐of‐life syndrome hypothesis, mass/energy fluxes should link behaviour and its plasticity with physiology at both between‐ and within‐individual levels. However, a mechanistic framework driving these links in a fluctuating ecological context is lacking. Focusing on home range behaviour, we propose a novel behavioural‐bioenergetics theoretical model to address such complexities at the individual level based on energy balance. We propose explicit mechanistic links between behaviour, physiology/metabolism and LH by merging two well‐founded theories, the movement ecology paradigm and the dynamic energetic budget theory. Overall, our behavioural‐bioenergetics model integrates the mechanisms explaining how (1) behavioural between‐ and within‐individual variabilities connect with internal state variable dynamics, (2) physiology and behaviour are explicitly interconnected by mass/energy fluxes, and (3) different LHs may arise from both behavioural and physiological variabilities in a given ecological context. Our novel theoretical model reveals encouraging opportunities for empiricists and theoreticians to delve into the eco‐evolutionary processes that favour or hinder the development of between‐individual differences in behaviour and the evolution of personality‐dependent movement syndromes.     

A dynamic model for finger interphalangeal coordination

In this paper a dynamic model to investigate interphalangeal coordination in the human finger is proposed. Suitable models which describe the relationship between the tendon displacement and the joint angles have been chosen and incorporated into the skeletal dynamic model. A kinematic and kinetic model for interphalangeal coordination is suggested. Digital computer simulations are carried out to study interphalangeal (IP) flexion. Moreover, the effect of two different optimization methods is contrasted. The two optimization algorithms are employed to obtain a set of feasible values for the forces in the tendons or muscles of the finger.     

Sensory and intrinsic coordination of movement

A recently generalized theory of perceptual guidance (general tau theory) was used to analyse coordination in skilled movement. The theory posits that (i) guiding movement entails controlling closure of spatial and/or force gaps between effectors and goals, by sensing and regulating the tau s of the gaps (the time-to-closure at current closure rate), (ii) a principal way of coordinating movements is keeping the tau s of different gaps in constant ratio (known as tau-coupling), and (iii) intrinsically paced movements are guided and coordinated by tau-coupling onto a tau-guide, tau g, generated in the nervous system and described by the equation tau g = 0.5 (t-T 2/t) where T is the duration of the body movement and t is the time from the start of the movement. Kinematic analysis of hand to mouth movements by human adults, with eyes open or closed, indicated that hand guidance was achieved by maintaining, during 80 85% of the movement, the tau-couplings tau alpha-tau r and tau r-tau g, where tau r is tau of the hand-mouth gap, tau alpha is tau of the angular gap to be closed by steering the hand and tau g is an intrinsic tau-guide.     

Visual perception: A dynamic theory

Perception is generally thought to occur centrally in the nervous system as a result of information which flows unidirectionally through a hierarchy of sensory processors. Such a view is in conflict with recent experimental evidence for a centrifugal control capable of enhancing particular features of the sensory input. Certain phenomena in human perception, resembling order-disorder transitions in physics, also suggest the existence of a positive feedback mechanism in the sensory pathway. A mechanism of perception is proposed in which unstructured feedback can accomplish the desired feature-specific enhancement of the input. The principle used here — the Alopex principle — is one that was devised in this laboratory for the experimental determination of visual receptive fields. The biological requirements for the operation of the principle are discussed, and a possible site in the thalamic relay nuclei is suggested.     

A dynamic Brownian bridge movement model to estimate utilization distributions for heterogeneous animal movement

1.?The recently developed Brownian bridge movement model (BBMM) has advantages over traditional methods because it quantifies the utilization distribution of an animal based on its movement path rather than individual points and accounts for temporal autocorrelation and high data volumes. However, the BBMM assumes unrealistic homogeneous movement behaviour across all data. 2.?Accurate quantification of the utilization distribution is important for identifying the way animals use the landscape. 3.?We improve the BBMM by allowing for changes in behaviour, using likelihood statistics to determine change points along the animal's movement path. 4.?This novel extension, outperforms the current BBMM as indicated by simulations and examples of a territorial mammal and a migratory bird. The unique ability of our model to work with tracks that are not sampled regularly is especially important for GPS tags that have frequent failed fixes or dynamic sampling schedules. Moreover, our model extension provides a useful one-dimensional measure of behavioural change along animal tracks. 5.?This new method provides a more accurate utilization distribution that better describes the space use of realistic, behaviourally heterogeneous tracks.     

A general dynamic theory of oceanic island biogeography

Aim MacArthur and Wilson’s dynamic equilibrium model of island biogeography provides a powerful framework for understanding the ecological processes acting on insular populations. However, their model is known to be less successful when applied to systems and processes operating on evolutionary and geological timescales. Here, we present a general dynamic model (GDM) of oceanic island biogeography that aims to provide a general explanation of biodiversity patterns through describing the relationships between fundamental biogeographical processes – speciation, immigration, extinction – through time and in relation to island ontogeny. Location Analyses are presented for the Azores, Canaries, Galápagos, Marquesas and Hawaii. Methods We develop a theoretical argument from first principles using a series of graphical models to convey key properties and mechanisms involved in the GDM. Based on the premises (1) that emergent properties of island biotas are a function of rates of immigration, speciation and extinction, (2) that evolutionary dynamics predominate in large, remote islands, and (3) that oceanic islands are relatively short‐lived landmasses showing a characteristic humped trend in carrying capacity (via island area, topographic variation, etc.) over their life span, we derive a series of predictions concerning biotic properties of oceanic islands. We test a subset of these predictions using regression analyses based largely on data sets for native species and single‐island endemics (SIEs) for particular taxa from each archipelago, and using maximum island age estimates from the literature. The empirical analyses test the power of a simple model of diversity derived from the GDM: the log(Area) + Time + Time² model (ATT²), relative to other simpler time and area models, using several diversity metrics. Results The ATT² model provides a more satisfactory explanation than the alternative models evaluated (for example the standard diversity–area models) in that it fits a higher proportion of the data sets tested, although it is not always the most parsimonious solution. Main conclusions The theoretical model developed herein is based on the key dynamic biological processes (migration, speciation, extinction) combined with a simple but general representation of the life cycle of oceanic islands, providing a framework for explaining patterns of biodiversity, endemism and diversification on a range of oceanic archipelagos. The properties and predictions derived from the model are shown to be broadly supported (1) by the empirical analyses presented, and (2) with reference to previous phylogenetic, ecological and geological studies.     

A stochastic theory of phase transitions in human hand movement

The order parameter equation for the relative phase of correlated hand movements, derived in a previous paper by Haken et al. (1985), is extended to a time-dependent stochastic differential equation. Its solutions are determined close to stationary points and for the transition region. Remarkably good agreement between this theory and recent experiments done by Kelso and Scholz (1985) is found, and new predictions are offered.     

A discrete dynamic model of a neuronal network with space-time organization]

A dynamical model of the neuronal network based on the principles of spatial-temporal organization of information processing was constructed. The additivity law for the formation of input connection factors in this model provides its versatility for a variety of logical functions. The model takes into account real properties of the systemic organization of brain neurones.     

A theory of dynamic and steady responses in chemoreception

A theoretical model which can account for both the dynamic and steady responses is proposed based on the occupation theory. The reaction scheme used is;

Here, S and A are stimulus chemicals and receptor sites unbound, respectively. The binding of S to A leads to an active complex (SA)_active, which is successively transformed into an inactive complex (SA)_active. The response is assumed to be proportional to number of (SA)_active. When a stimulating solution is applied instantaneously at t = 0, the solution to the set of differential equations based on the above scheme is obtained as follows;

where p and C stand for the fraction of (SA)_active to the total number of receptor sites and stimulus concentration, respectively, and α_i, and ω_i (i = 1, 2) are numerical parameters depending on the rate constants and on C. The steady response is expressed as the third term in the above equation, which indicates that the response accords with the Beidler taste equation. Mathematical analysis of the above scheme shows that the dynamic response appears when k₁C > k_?2, and the calculated results for the dynamic response agree approximately with the Hill equation. The Hill coefficient lays within 1·00 and 0·79 and reaches unity with increasing $\text{k}{}_{\mathrm{?1}}\text{k}{}_2$, which implies that the dynamic response under this condition satisfies the Beidler taste equation. For the case of gradual application of stimuli, i.e. the experimental condition, the time course of p is simulated with use of an analogue computer rather than with a numerical solution to the above equation. The results indicate that the dynamic response diminishes with decreasing the application speed of stimulus solution. The present theory accounts consistently for various experimental data observed in the chemoreceptor systems.     

A two-step EMG-and-optimization process to estimate muscle force during dynamic movement

The present study proposed a two-step EMG-and-optimization method for muscle force estimation in dynamic condition. Considering the strengths and the limitations of existing methods, the proposed approach exploited the advantages of min/max optimization with constraints on the contributions of the flexor and extensor muscle groups to the net joint moment estimated through an EMG-to-moment approach. Our methodology was tested at the knee joint during dynamic half squats, and was compared with traditional min/max optimization. In general, results showed significant differences in muscle force estimates from EMG-and-optimization method when compared with those from traditional min/max optimization. Muscle forces were higher – especially in the antagonist muscles – and more consistent with EMG patterns because of the ability of the proposed approach to properly account for agonist/antagonist cocontraction. In addition, muscle forces agree with mechanical constraints regarding the net, the agonist, and the antagonist moments, thus greatly improving the confidence in muscle force estimates. The proposed two-step EMG-and-optimization method for muscle force estimation is easy to implement with relatively low computational requirements and, thus, could offer interesting advantages for various applications in many fields, including rehabilitation, clinical, and sports biomechanics.