Multistability, cross-modal binding and the additivity of conjoined grouping principles

We present a sceptical view of multimodal multistability--drawing most of our examples from the relation between audition and vision. We begin by summarizing some of the principal ways in which audio-visual binding takes place. We review the evidence that unambiguous stimulation in one modality may affect the perception of a multistable stimulus in another modality. Cross-modal influences of one multistable stimulus on the multistability of another are different: they have occurred only in speech perception. We then argue that the strongest relation between perceptual organization in vision and perceptual organization in audition is likely to be by way of analogous Gestalt laws. We conclude with some general observations about multimodality.     

Asymmetric and transient properties of reciprocal activity of antagonists during the paw-shake response in the cat

Mutually inhibitory populations of neurons, half-center oscillators (HCOs), are commonly involved in the dynamics of the central pattern generators (CPGs) driving various rhythmic movements. Previously, we developed a multifunctional, multistable symmetric HCO model which produced slow locomotor-like and fast paw-shake-like activity patterns. Here, we describe asymmetric features of paw-shake responses in a symmetric HCO model and test these predictions experimentally. We considered bursting properties of the two model half-centers during transient paw-shake-like responses to short perturbations during locomotor-like activity. We found that when a current pulse was applied during the spiking phase of one half-center, let’s call it #1, the consecutive burst durations (BDs) of that half-center increased throughout the paw-shake response, while BDs of the other half-center, let’s call it #2, only changed slightly. In contrast, the consecutive interburst intervals (IBIs) of half-center #1 changed little, while IBIs of half-center #2 increased. We demonstrated that this asymmetry between the half-centers depends on the phase of the locomotor-like rhythm at which the perturbation was applied. We suggest that the fast transient response reflects functional asymmetries of slow processes that underly the locomotor-like pattern; e.g., asymmetric levels of inactivation across the two half-centers for a slowly inactivating inward current. We compared model results with those of in-vivo paw-shake responses evoked in locomoting cats and found similar asymmetries. Electromyographic (EMG) BDs of anterior hindlimb muscles with flexor-related activity increased in consecutive paw-shake cycles, while BD of posterior muscles with extensor-related activity did not change, and vice versa for IBIs of anterior flexors and posterior extensors. We conclude that EMG activity patterns during paw-shaking are consistent with the proposed mechanism producing transient paw-shake-like bursting patterns found in our multistable HCO model. We suggest that the described asymmetry of paw-shaking responses could implicate a multifunctional CPG controlling both locomotion and paw-shaking.     

Two-phase strategy of controlling motor coordination determined by task performance optimality

A quantitative model of optimal coordination between hand transport and grip aperture has been derived in our previous studies of reach-to-grasp movements without utilizing explicit knowledge of the optimality criterion or motor plant dynamics. The model’s utility for experimental data analysis has been demonstrated. Here we show how to generalize this model for a broad class of reaching-type, goal-directed movements. The model allows for measuring the variability of motor coordination and studying its dependence on movement phase. The experimentally found characteristics of that dependence imply that execution noise is low and does not affect motor coordination significantly. From those characteristics it is inferred that the cost of neural computations required for information acquisition and processing is included in the criterion of task performance optimality as a function of precision demand for state estimation and decision making. The precision demand is an additional optimized control variable that regulates the amount of neurocomputational resources activated dynamically. It is shown that an optimal control strategy in this case comprises two different phases. During the initial phase, the cost of neural computations is significantly reduced at the expense of reducing the demand for their precision, which results in speed-accuracy tradeoff violation and significant inter-trial variability of motor coordination. During the final phase, neural computations and thus motor coordination are considerably more precise to reduce the cost of errors in making a contact with the target object. The generality of the optimal coordination model and the two-phase control strategy is illustrated on several diverse examples.     

Impairments of social motor coordination in schizophrenia

It has been demonstrated that motor coordination of interacting people plays a crucial role in the success of social exchanges. Abnormal movements have been reported during interpersonal interactions of patients suffering from schizophrenia and a motor coordination breakdown could explain this social interaction deficit, which is one of the main and earliest features of the illness. Using the dynamical systems framework, the goal of the current study was (i) to investigate whether social motor coordination is impaired in schizophrenia and (ii) to determine the underlying perceptual or cognitive processes that may be affected. We examined intentional and unintentional social motor coordination in participants oscillating hand-held pendulums from the wrist. The control group consisted of twenty healthy participant pairs while the experimental group consisted of twenty participant pairs that included one participant suffering from schizophrenia. The results showed that unintentional social motor coordination was preserved while intentional social motor coordination was impaired. In intentional coordination, the schizophrenia group displayed coordination patterns that had lower stability and in which the patient never led the coordination. A coupled oscillator model suggests that the schizophrenia group coordination pattern was due to a decrease in the amount of available information together with a delay in information transmission. Our study thus identified relational motor signatures of schizophrenia and opens new perspectives for detecting the illness and improving social interactions of patients.     

The discontinuous nature of motor execution

Human movement control requires adequate coordination of different movements, which is particularly important when different motor tasks are simultaneously executed by the same effector(s) (e.g. a muscle or a joint). The process of movement execution involves a series of highly nonlinear elements; for instance, a motor unit of a muscle produces force only in the direction of muscle shortening, thus representing a threshold operator that transforms the bipolar (i.e. excitatory or inhibitory) information at its spinal input into a purely unipolar signal (i.e. muscle force). This tripartite research report addresses the contribution of the nonlinearity of neuromuscular elements to the coordination of different motor tasks simultaneously executed by the same limb. In this first part of the series, a new hypothesis for such a single-muscle multiple-task coordination is presented which suggests an essentially threshold-linear coordination mechanism. Control signals generated by the central nervous system for each individual movement independently and feedback information from peripheral receptors are linearly superimposed. This compound control/feedback signal is processed by a nonlinear limiter element reflecting the discontinuous properties of the muscle and its reflex circuitry. It is shown that threshold-linear interaction of descending commands and afferent feedback information can lead to complex interdependent patterns of compound motor action. This includes the possibility of gating (i.e. the ability of one movement pattern to constrain or even impede the execution of another pattern) and of delayed response initiation when simultaneously performing more than one voluntary motor task. A theoretical analysis of the threshold-linear coordination mechanism and an extensive experimental validation of the model is provided in part II and part III of the report. Received: 6 October 1998 / Accepted in revised form: 2 June 1999     

Descending interneurones from the brain and suboesophageal ganglia and their role in the control of locust behaviour

Lesion and stimulation experiments suggest that the suboesophageal ganglion (SOG) plays a special role in the control of insect behaviour: in bilateral coordination and by maintaining ongoing motor activity. Anatomical observations indicate that there are descending interneurones (DINs) originating in the SOG in addition to those from the brain. An SOG preparation for sampling both types of DIN intracellularly in walking locusts is described. Forty-three units showing activity changes during leg movements and walking were recorded. Using dye injection six were shown to be through-running axons; one was an SOG ascending interneurone; and eight were SOG DINs, 7 contralateral, one ipsilateral. All fired before or during movements and received various sensory inputs. Many gave complex responses to different modalities, several showing directional preferences. Some SOG neurones showed spontaneous changes in activity; activity outlasting movements; or responses to passive as well as active movements. These preliminary results suggest neuronal substrates for the special functions of the SOG in behaviour. They also indicate that DINs, rather than being simple relays, are part of a dynamic network which includes the motor centres. Regulation of complex and subtle aspects of behaviour may be achieved by dynamic and sequential patterns of activity in groups of DINs, some of which may be multifunctional.     

Normalized Index of Synergy for Evaluating the Coordination of Motor Commands

Humans perform various motor tasks by coordinating the redundant motor elements in their bodies. The coordination of motor outputs is produced by motor commands, as well properties of the musculoskeletal system. The aim of this study was to dissociate the coordination of motor commands from motor outputs. First, we conducted simulation experiments where the total elbow torque was generated by a model of a simple human right and left elbow with redundant muscles. The results demonstrated that muscle tension with signal-dependent noise formed a coordinated structure of trial-to-trial variability of muscle tension. Therefore, the removal of signal-dependent noise effects was required to evaluate the coordination of motor commands. We proposed a method to evaluate the coordination of motor commands, which removed signal-dependent noise from the measured variability of muscle tension. We used uncontrolled manifold analysis to calculate a normalized index of synergy. Simulation experiments confirmed that the proposed method could appropriately represent the coordinated structure of the variability of motor commands. We also conducted experiments in which subjects performed the same task as in the simulation experiments. The normalized index of synergy revealed that the subjects coordinated their motor commands to achieve the task. Finally, the normalized index of synergy was applied to a motor learning task to determine the utility of the proposed method. We hypothesized that a large part of the change in the coordination of motor outputs through learning was because of changes in motor commands. In a motor learning task, subjects tracked a target trajectory of the total torque. The change in the coordination of muscle tension through learning was dominated by that of motor commands, which supported the hypothesis. We conclude that the normalized index of synergy can be used to evaluate the coordination of motor commands independently from the properties of the musculoskeletal system.     

On a Nonlinear Master Equation and the Haken-Kelso-Bunz Model

A nonlinear master equation (NLME) is proposed basedon general information measures.Classical and cut-off solutions of the NLME are considered.In the former case, the NLME exhibits uniquely defined stationary distributions. In the latter case, there are multiple stationary distributions.In particular, for classical solutions, it is shown that transient solutions converge to stationary distributions that maximize information measures (H-theorem). Cut-off distributions arestudied numerically for the Haken-Kelso-Bunz model. The Haken-Kelso-Bunz modelis known to describe multistable human motor control systems. It is shownthat a stochastic Haken-Kelso-Bunz model based on a NLME can exhibit multiplestationary cut-off distributions.In doing so, we illustrate that multistability in stochastic biological systems can beestablished by means of cut-off distributions.     

Motor networks: shifting coalitions

Are central motor networks composed of task-specific dedicated neurons or are the neurons multifunctional, entering shifting coalitions for particular tasks to form different functional networks? Recent experiments elegantly indicate the latter.     

Coordination of Fictive Motor Activity in the Larval Zebrafish Is Generated by Non-Segmental Mechanisms

The cellular and network basis for most vertebrate locomotor central pattern generators (CPGs) is incompletely characterized, but organizational models based on known CPG architectures have been proposed. Segmental models propose that each spinal segment contains a circuit that controls local coordination and sends longer projections to coordinate activity between segments. Unsegmented/continuous models propose that patterned motor output is driven by gradients of neurons and synapses that do not have segmental boundaries. We tested these ideas in the larval zebrafish, an animal that swims in discrete episodes, each of which is composed of coordinated motor bursts that progress rostrocaudally and alternate from side to side. We perturbed the spinal cord using spinal transections or strychnine application and measured the effect on fictive motor output. Spinal transections eliminated episode structure, and reduced both rostrocaudal and side-to-side coordination. Preparations with fewer intact segments were more severely affected, and preparations consisting of midbody and caudal segments were more severely affected than those consisting of rostral segments. In reduced preparations with the same number of intact spinal segments, side-to-side coordination was more severely disrupted than rostrocaudal coordination. Reducing glycine receptor signaling with strychnine reversibly disrupted both rostrocaudal and side-to-side coordination in spinalized larvae without disrupting episodic structure. Both spinal transection and strychnine decreased the stability of the motor rhythm, but this effect was not causal in reducing coordination. These results are inconsistent with a segmented model of the spinal cord and are better explained by a continuous model in which motor neuron coordination is controlled by segment-spanning microcircuits.     

Schema-based learning of adaptable and flexible prey-catching in anurans I. The basic architecture

A motor action often involves the coordination of several motor synergies and requires flexible adjustment of the ongoing execution based on feedback signals. To elucidate the neural mechanisms underlying the construction and selection of motor synergies, we study prey-capture in anurans. Experimental data demonstrate the intricate interaction between different motor synergies, including the interplay of their afferent feedback signals (Weerasuriya 1991; Anderson and Nishikawa 1996). Such data provide insights for the general issues concerning two-way information flow between sensory centers, motor circuits and periphery in motor coordination. We show how different afferent feedback signals about the status of the different components of the motor apparatus play a critical role in motor control as well as in learning. This paper, along with its companion paper, extend the model by Liaw et al. (1994) by integrating a number of different motor pattern generators, different types of afferent feedback, as well as the corresponding control structure within an adaptive framework we call Schema-Based Learning. We develop a model of the different MPGs involved in prey-catching as a vehicle to investigate the following questions: What are the characteristic features of the activity of a single muscle? How can these features be controlled by the premotor circuit? What are the strategies employed to generate and synchronize motor synergies? What is the role of afferent feedback in shaping the activity of a MPG? How can several MPGs share the same underlying circuitry and yet give rise to different motor patterns under different input conditions? In the companion paper we also extend the model by incorporating learning components that give rise to more flexible, adaptable and robust behaviors. To show these aspects we incorporate studies on experiments on lesions and the learning processes that allow the animal to recover its proper functioning     

Dynamics of hemispheric specialization and integration in the context of motor control

Behavioural and neurophysiological evidence convincingly establish that the left hemisphere is dominant for motor skills that are carried out with either hand or those that require bimanual coordination. As well as this prioritization, we argue that specialized functions of the right hemisphere are also indispensable for the realization of goal-directed behaviour. As such, lateralization of motor function is a dynamic and multifaceted process that emerges across different timescales and is contingent on task- and performer-related determinants.     

Multistability and dynamic transitions of intracellular Min protein patterns

Cells owe their internal organization to self‐organized protein patterns, which originate and adapt to growth and external stimuli via a process that is as complex as it is little understood. Here, we study the emergence, stability, and state transitions of multistable Min protein oscillation patterns in live Escherichia coli bacteria during growth up to defined large dimensions. De novo formation of patterns from homogenous starting conditions is observed and studied both experimentally and in simulations. A new theoretical approach is developed for probing pattern stability under perturbations. Quantitative experiments and simulations show that, once established, Min oscillations tolerate a large degree of intracellular heterogeneity, allowing distinctly different patterns to persist in different cells with the same geometry. Min patterns maintain their axes for hours in experiments, despite imperfections, expansion, and changes in cell shape during continuous cell growth. Transitions between multistable Min patterns are found to be rare events induced by strong intracellular perturbations. The instances of multistability studied here are the combined outcome of boundary growth and strongly nonlinear kinetics, which are characteristic of the reaction–diffusion patterns that pervade biology at many scales.     

Premotor interneurons in generation of adaptive leg reflexes and voluntary movements in stick insects

We investigated the role of local nonspiking interneurons involved in motor control of legs in the stick insect, Carausius morosus. In a preparation that allowed the animals to perform active leg movements such as adaptive tactile reflexes, proprioceptive reflexes, and walking, we gathered the following results. Almost all tested nonspiking interneurons that provide synaptic drive onto motoneurons of the proximal leg muscles contribute to all of the motor programs underlying tactile reflexes and voluntary leg movements such as walking, searching, and rocking. Most of them are also involved in the generation of proprioceptive reflexes. All motor programs for coactivation, avoidance reflexes, resistance reflexes, and voluntary leg movements result from parallel pathways including nonspiking interneurons that support and others that oppose the motoneuronal activity. The contribution of a single interneuron to the different motor programs is specific: it can be supporting for one motor program but opposing for the other. Even for the same motor program, for example, coactivation, the contribution of an individual interneuron can depend on the stimulus site from where the response is elicited. Our results support the idea that the different motor patterns for adaptive tactile reflexes, resistance reflexes, and voluntary leg movements emerge from a multifunctional neuronal circuit that is reorganized corresponding to the motor behavior performed. The actual motor pattern is then shaped by distributed information processing in parallel supporting and opposing pathways. © 1996 John Wiley & Sons, Inc.     

Deterministic analysis of stochastic bifurcations in multi-stable neurodynamical systems

Many perceptual and cognitive processes, like decision-making and bistable perception, involve multistable phenomena under the influence of noise. The role of noise in a multistable neurodynamical system can be formally treated within the Fokker–Planck framework. Nevertheless, because of the underlying nonlinearities, one usually considers numerical simulations of the stochastic differential equations describing the original system, which are time consuming. An alternative analytical approach involves the derivation of reduced deterministic differential equations for the moments of the distribution of the activity of the neuronal populations. The study of the reduced deterministic system avoids time consuming computations associated with the need to average over many trials. We apply this technique to describe multistable phenomena. We show that increasing the noise amplitude results in a shifting of the bifurcation structure of the system.     

Bifurcation study of a neural field competition model with an application to perceptual switching in motion integration

Perceptual multistability is a phenomenon in which alternate interpretations of a fixed stimulus are perceived intermittently. Although correlates between activity in specific cortical areas and perception have been found, the complex patterns of activity and the underlying mechanisms that gate multistable perception are little understood. Here, we present a neural field competition model in which competing states are represented in a continuous feature space. Bifurcation analysis is used to describe the different types of complex spatio-temporal dynamics produced by the model in terms of several parameters and for different inputs. The dynamics of the model was then compared to human perception investigated psychophysically during long presentations of an ambiguous, multistable motion pattern known as the barberpole illusion. In order to do this, the model is operated in a parameter range where known physiological response properties are reproduced whilst also working close to bifurcation. The model accounts for characteristic behaviour from the psychophysical experiments in terms of the type of switching observed and changes in the rate of switching with respect to contrast. In this way, the modelling study sheds light on the underlying mechanisms that drive perceptual switching in different contrast regimes. The general approach presented is applicable to a broad range of perceptual competition problems in which spatial interactions play a role.     

Cluster structure of the psychomotor and coordination spheres in younger schoolchildren

The goal of this study was to describe typical motor profiles in younger schoolchildren. A total of 89 subjects aged 8–10 years, students of primary schools of Moscow not going in for sports took part in the study. Twenty-five indices of psychophysiological (NS-PsihoTest), psychomotor (KID-3), posturography and locomotor tests (nine coordination tests) have been measured. According to their motor coordination, the children have been subdivided into groups using k-means cluster analysis. The four obtained clusters are supposed to reflect different types of motor coordination and correspond to four individual motor profiles typical of children aged 8–10 years. These motor coordination types were not associated with age, sex, or constitution; therefore, they may be promising for selecting sports. The ability to anticipate and a high speed of wrist movement were typical of children from the first cluster. Subjects from the second cluster were more successful in rapid, rhythmic, and automatic actions, based on the mechanism of intrinsic programming. Subjects from the third cluster displayed a moderate ability of postural control, but at the same time, they were characterized by smooth, accurate, and rhythmic arm actions based on visual feedback, and an advanced sense of rhythm and space sense. Subjects from the fourth cluster were the most coordinated ones, which is important for sports and occupational activities requiring a high level of coordination.     

The molecular bases of spinal muscular atrophy

Spinal muscular atrophy (SMA) is a common recessive autosomal disorder characterized by degeneration of motor neurons of the spinal cord. SMA is caused by mutations of the survival of motor neuron gene that encodes a multifunctional protein, and mouse models have been generated. These advances represent starting points towards an understanding of the pathophysiology of this disease and the design of therapeutic strategies in SMA.     

Role of motor cortex in coordinating multi-joint movements: is it time for a new paradigm?

Reaching movements to spatial targets require motor patterns at the shoulder to be coordinated carefully with those at the elbow to smoothly move the hand through space. While the motor cortex is involved in this volitional task, considerable debate remains about how this cortical region participates in planning and controlling movement. This article reviews two opposing interpretations of motor cortical function during multi-joint movements. On the one hand, studies performed predominantly on single-joint movement generally support the notion that motor cortical activity is intimately involved in generating motor patterns at a given joint. In contrast, studies on reaching demonstrate correlations between motor cortical activity and features of movement related to the hand, suggesting that the motor cortex may be involved in more global features of the task. Although this latter paradigm involves a multi-joint motor task in which neural activity is correlated with features of movement related to the hand, this neural activity is also correlated to other movement variables. Therefore it is difficult to assess if and how the motor cortex contributes to the coordination of motor patterns at different joints. In particular, present paradigms cannot assess whether motor cortical activity contributes to the control of one joint or multiple joints during whole-arm tasks. The final point discussed in this article is the development of a new experimental device (KINARM) that can both monitor and manipulate the mechanics of the shoulder and elbow independently during multi-joint motor tasks. It is hoped that this new device will provide a new approach for examining how the motor cortex is involved in motor coordination.     

Stochasticity,Bistability and the Wisdom of Crowds: A Model for Associative Learning in Genetic Regulatory Networks

It is generally believed that associative memory in the brain depends on multistable synaptic dynamics, which enable the synapses to maintain their value for extended periods of time. However, multistable dynamics are not restricted to synapses. In particular, the dynamics of some genetic regulatory networks are multistable, raising the possibility that even single cells, in the absence of a nervous system, are capable of learning associations. Here we study a standard genetic regulatory network model with bistable elements and stochastic dynamics. We demonstrate that such a genetic regulatory network model is capable of learning multiple, general, overlapping associations. The capacity of the network, defined as the number of associations that can be simultaneously stored and retrieved, is proportional to the square root of the number of bistable elements in the genetic regulatory network. Moreover, we compute the capacity of a clonal population of cells, such as in a colony of bacteria or a tissue, to store associations. We show that even if the cells do not interact, the capacity of the population to store associations substantially exceeds that of a single cell and is proportional to the number of bistable elements. Thus, we show that even single cells are endowed with the computational power to learn associations, a power that is substantially enhanced when these cells form a population.