Einat Fuchs

Intersegmental coordination of cockroach locomotion: adaptive control of centrally coupled pattern generator circuits

Animals’ ability to demonstrate both stereotyped and adaptive locomotor behavior is largely dependent on the interplay between centrally generated motor patterns and the sensory inputs that shape them. We utilized a combined experimental and theoretical approach to investigate the relative importance of CPG interconnections vs. intersegmental afferents in the cockroach: an animal that is renowned for rapid and stable locomotion. We simultaneously recorded coxal levator and depressor motor neurons (MN) in the thoracic ganglia of Periplaneta americana, while sensory feedback was completely blocked or allowed only from one intact stepping leg. In the absence of sensory feedback, we observed a coordination pattern with consistent phase relationship that shares similarities with a double-tripod gait, suggesting central, feedforward control. This intersegmental coordination pattern was then reinforced in the presence of sensory feedback from a single stepping leg. Specifically, we report on transient stabilization of phase differences between activity recorded in the middle and hind thoracic MN following individual front-leg steps, suggesting a role for afferent phasic information in the coordination of motor circuits at the different hemiganglia. Data were further analyzed using stochastic models of coupled oscillators and maximum likelihood techniques to estimate underlying physiological parameters, such as uncoupled endogenous frequencies of hemisegmental oscillators and coupling strengths and directions. We found that descending ipsilateral coupling is stronger than ascending coupling, while left–right coupling in both the meso- and meta-thoracic ganglia appear to be symmetrical. We discuss these results in comparison with recent findings in stick insects that share similar neural and body architectures, and argue that the two species may exemplify opposite extremes of a fast–slow locomotion continuum, mediated through different intersegment coordination strategies.

Proprioceptive feedback reinforces centrally generated stepping patterns in the cockroach

SUMMARY The relative importance of sensory input for the production of centrally generated motor patterns is crucial to our understanding of how animals coordinate their body segments to locomote. In legged locomotion, where terrain heterogeneity may require stride-by-stride changes in leg placement, evidence suggests that sensory information is essential for the timing of leg movement. In a previous study we showed that in cockroaches, renowned for rapid and stable running, a coordinated pattern can be elicited from the motor centres driving the different legs in the absence of sensory feedback. In the present paper, we assess the role of movement-related sensory inputs in modifying this central pattern. We studied the effect of spontaneous steps as well as imposed transient and periodic movements of a single intact leg, and demonstrate that, depending on the movement properties, the resulting proprioceptive feedback can significantly modify phase relationships among segmental oscillators of other legs. Our analysis suggests that feedback from front legs is weaker but more phasically precise than from hind legs, selectively transferring movement-related information in a manner that strengthens the inherent rhythmic pattern and modulates local perturbations.

The formation of synchronization cliques during the development of modular neural networks

Modular organization is a special feature shared by many biological and social networks alike. It is a hallmark for systems exhibiting multitasking, in which individual tasks are performed by separated and yet coordinated functional groups. Understanding how networks of segregated modules develop to support coordinated multitasking functionalities is the main topic of the current study. Using simulations of biologically inspired neuronal networks during development, we study the formation of functional groups (cliques) and inter-neuronal synchronization. The results indicate that synchronization cliques first develop locally according to the explicit network topological organization. Later on, at intermediate connectivity levels, when networks have both local segregation and long-range integration, new synchronization cliques with distinctive properties are formed. In particular, by defining a new measure of synchronization centrality, we identify at these developmental stages dominant neurons whose functional centrality largely exceeds the topological one. These are generated mainly in a few dominant clusters that become the centers of the newly formed synchronization cliques. We show that by the local synchronization properties at the very early developmental stages, it is possible to predict with high accuracy which clusters will become dominant in later stages of network development.

Contextual regularity and complexity of neuronal activity: from stand-alone cultures to task-performing animals

Precursors of the superior information processing capabilities of our cortex can most probably be traced back to simple invertebrate systems. Using a unique set of newly developed neuronal preparations and state-of-the-art analysis tools, we show that insect neurons have the ability to self-regulate the information capacity of their electrical activity. We characterize the activity of a distinct population of neurons under progressive levels of structural and functional constraints: self-formed networks of neuron clusters in vitro; isolated ex vivo ganglions; in vivo task-free, and in vivo task-forced neuronal activity in the intact animal. We show common motifs and identify trends of increasing self-regulated complexity. This important principle may have played a key role in the gradual transition from simple neuronal motor control to complex information processing.

The function of intersegmental connections in determining temporal characteristics of the spinal cord rhythmic output

Recent renewed interest in the study of rhythmic behaviors and pattern-generating circuits has been inspired by the currently well-established role of oscillating neuronal networks in all aspects of the function of our nervous system: from sensory integration to central processing, and of course motor control. An integrative rather than reductionist approach in the study of pattern-generating circuits is in accordance with current developments. The lamprey spinal cord, a relatively simple and much-studied preparation, is a useful model for such a study. It is an example of a chain of coupled oscillatory units that is characterized by its ability to demonstrate robust coordinated rhythmic output when isolated in vitro. The preparation allows maximum control over the chemical (neuromodulators and hormones) as well as neuronal environment (sensory and descending inputs) of the single oscillatory unit: the pattern-generating circuit. The current study made use of recently developed tools for nonlinear analysis of time-series, specifically neurophysiological signals. These tools allow us to reveal and characterize biological-functional complexity and information capacity of the neuronal output recorded from the lamprey model network. We focused on the importance of different types of inputs to an oscillatory network and their effect on the networks functional output. We show that the basic circuit, when isolated from short- and long-range neuronal inputs, demonstrates its full potential of information capacity: maximal variation quantities and elevated functional complexity. Morphological and functional constraints result in the network exhibiting only a limited range of the above. This constitutes an important substrate for plasticity in neuronal network function.