Spinal pattern generation and sensory gating mechanisms

Sensory gating mechanisms are deployed during vertebrate locomotion to ensure that adaptive and appropriate motor responses to afferent input occur during all phases of the movement cycle. Recent animal studies on the integration of cutaneous information have investigated the roles of interneurones in sensory gating. Premotor interneurones, rhythmically active during locomotion, as well as 'sensory' interneurones appear to be intimately involved in sensory gating, receiving synaptic inputs from the spinal rhythm generator to gate the flow of sensory information in the spinal cord.     

Motor pattern generation

Recent work on the circuits that generate rhythmic movements illustrates the role of cotransmitter complement in motor pattern selection and demonstrates that many principles first established in invertebrates also hold in vertebrates. Major new areas of investigation include the development of central pattern generating networks, and the use of mouse mutants.     

Invertebrate central pattern generation moves along

Central pattern generators (CPGs) are circuits that generate organized and repetitive motor patterns, such as those underlying feeding, locomotion and respiration. We summarize recent work on invertebrate CPGs which has provided new insights into how rhythmic motor patterns are produced and how they are controlled by higher-order command and modulatory interneurons.     

Synaptic mechanisms in invertebrate pattern generation

Although individual neurons can be intrinsically oscillatory and can be network pacemakers, motor patterns are often generated in a more distributed manner. Synaptic connections with other neurons are important because they either modify the rhythm of the pacemaker cell or are essential for pattern generation in the first place. Computational studies of half-center oscillators have made much progress in describing how neurons make transitions between active and inactive phases in these simple networks. In addition to characterizing phase transitions, recent studies have described the synaptic mechanisms that are important for the initiation and maintenance of activity in half-center oscillators.     

A synergic approach to plant pattern generation

The paper shows convergences between the results found in various models of phyllotaxis. It shows that a synergic approach is needed to deal with the problems of phyllotaxis. An algorithm, called the phi-model, based on the observation of the meaningful and symmetry-generating presence of the golden ratio phi in all types of spiral patterns, and consequently in all types of regular patterns in phyllotaxis, is proposed. The model is suggested by a property of the allometry-type model for pattern recognition in phyllotaxis. It extends recent morphological models developed around the idea of packing efficiency of plant primordia, models that yield the noble numbers, among which are the divergence angles of spiral patterns. The phi-model also gives the noble numbers and moreover orders them in a way that establishes connections with the morphogenetic principles used in models for pattern generation; the order has to do with the relative frequencies of the spiral patterns in nature. The phi-model is a link between the two entropy models in phyllotaxis and offers a nice correspondence with the minimal entropy model generated by a systemic and holistic approach. This latter type of approach is put forward as being able to give a general framework in which to organize the concepts, results, and models in phyllotaxis in a way that produces a synergy of efforts. The necessity of doing so is seen clearly when one considers that phyllotaxis-like patterns are encountered in other fields of research, so that the problem appears to transcend the strict botanical substratum.     

Finding differentially expressed genes for pattern generation

MOTIVATION: It is important to consider finding differentially expressed genes in a dataset of microarray experiments for pattern generation. RESULTS: We developed two methods which are mainly based on the q-values approach; the first is a direct extension of the q-values approach, while the second uses two approaches: q-values and maximum-likelihood. We present two algorithms for the second method, one for error minimization and the other for confidence bounding. Also, we show how the method called Patterns from Gene Expression (PaGE) (Grant et al., 2000) can benefit from q-values. Finally, we conducted some experiments to demonstrate the effectiveness of the proposed methods; experimental results on a selected dataset (BRCA1 vs BRCA2 tumor types) are provided. CONTACT: alhajj@cpsc.ucalgary.ca.     

A simple model of dynamic receptor pattern generation

A dynamic pattern generating automaton has been constructed. The rules controlling its function furnish the non-random generation of sub-patterns in consecutive cycles, within a large plane area, covered by four different classes of units of constant mean frequency in each class (standard system). The stabilization of certain specific sub-patterns over 100 subsequent cycles of pattern generation (modified systems) resulted in the modification of the frequency and frequency distribution of the sub-patterns relative to the standard system. Some new types of sub-patterns, not encountered in the standard system, also made appearance in the modified systems. The functioning of the standard and modified systems was analyzed and compared by the methods of mathematical statistics. The automaton was used to model certain features of the cytoplasmic membrane. The latter was regarded as a device by which the cell collects information about its environment. The dynamic generation of sub-patterns was taken as the cell's manner of asking questions, and the complementary chemical structures present in the environment were treated as possible answers to these. The irreversible question-answer interactions were regarded as signals and were modelled by the stabilization of specific sub-patterns. It was found that in a dynamic system like the model presented, it is not necessary to code each possible sub-pattern individually. Precise coding of the relative frequency of units per class and of their possible interactions is sufficient to furnish statistically constant mean frequencies for a given range of sub-patterns. In a dynamic system, the actual range of sub-patterns arisen in a population of identical individuals depends only on the size of the population. If the latter is appropriately large, all possible sub-patterns may be simultaneously present at any time at the average frequencies characteristic of each. Stabilized sub-patterns (signals) seem to modify specifically the frequencies of the other sub-patterns generated by the normal automaton. Some sub-patterns may disappear permanently, while others (new ones) may turn up and persist at given frequencies. Missense signals may definitively put the automaton out of order, i.e. result in the cell's complete misorientation in respect of its relations to the normal tissue structure.Reader of publications in physics, Gondolat Publishing House, Budapest, Hungary     

Central pattern generation underlying Limulus rhythmic behavior patterns

<正> Many behavioral activities of the horseshoe crab Limulus are rhythmic, and most of these are produced in large partby central pattern generators within the CNS. The chain of opisthosomal ('abdominal') ganglia controls gill movements of ventilationand gill cleaning, and the prosomal ring of fused ganglia (brain and segmental 'thoracic' ganglia) controls generation offeeding and locomotor movements of the legs. Both the opisthosomal CNS and the prosomal CNS can generate behaviorally appropriatepatterns of motor output in isolation, without movements or sensory input. Preparations of the isolated opisthosomalCNS generate rhythmic output patterns of motor activity characterized as fictive ventilatory and gill cleaning rhythms. Moreover,CNS preparations also express longer-term patterns, such as intermittent ventilation or sequential bouts of ventilation and gillcleaning. Such longer-term patterns are commonly observed in intact animals. The isolated prosomal CNS does not spontaneouslygenerate the activity patterns characteristic of walking, swimming, and feeding. However, perfusion of octopamine in the isolatedprosomal CNS activates central pattern generators underlying rhythmic chewing movements, and injection of octopamine into intactLimulus promotes the chewing pattern of feeding, whether or not food is presented. Our understanding of the ability of neuromodulatorssuch as octopamine to elicit or alter central motor programs may help to clarify the central neural circuits of patterngeneration that produce and coordinate these rhythmic behaviors     

A model of pattern generation of cockroach walking reconsidered

Cockroaches that have been decapitated or that have cut thoracic connectives can show rhythmic bursting in motoneurons to intrinsic leg muscles. These preparations have been studied as models for walking and to evaluate the functions of leg proprioceptors. The present study demonstrates that headless cockroaches walk extremely poorly and slowly with considerable discoordination of motoneuronal activity, these preparations show rhythmic motoneuron bursting that is similar to righting responses (attempts to turn upright) of intact animals when placed on their backs, and bursting is inhibited when a headless animal is turned or turns itself upright. Thus, rhythmic motoneuron activity of these preparations is most probably attempted righting rather than walking. It is concluded that the headless cockroach is useful for understanding the motor mechanisms underlying righting and walking but is not of value in assessing the functions of proprioceptive feedback.     

Cell interactions in the generation of chaetae pattern inDrosophila

Summary We have already shown that theachaetae-scute complex (AS-C) ofDrosophila is regulated by two genes,hairy andextramacrochaetae. Using mutants in these genes, we have analysed how different levels of expression of AS-C affect the pattern of chaetae. The results indicate that the spatial distribution of chaetae results from cell interactions, probably by a mechanism of lateral inhibition. The results are discussed in view of the different theories of pattern formation.     

Impulse pattern generation in a crayfish abdominal postural motoneuron

Journal of Comparative Physiology A - It is concluded that burst formation is endogenous to the motoneuron andnot strongly dependent on patterned presynaptic input.     

Central respiratory pattern generation in the bullfrog, Rana catesbeiana

There are two components to breathing pattern generation the production of the pattern of neural discharge associated with individual breaths, and the pattern in which breaths are produced to effect ventilation. Bullfrogs typically breathe with randomly distributed breaths. When respiratory drive is elevated, breathing becomes more regular and often episodic. Studies on in vitro brainstem-spinal cord preparations of the adult bullfrog and in situ preparations of decerebrate, paralyzed, unidirectionally ventilated animals suggest that output from the central rhythm generator in frogs is conditional on receiving some input and that a host of central inputs remain even in the most reduced preparations. There appear to be descending inputs from sites in the dorsal brainstem just caudal to the optic chiasma that cluster breaths into episodes, a strong excitatory input caudal to this site but rostral to the origin of the Vth cranial nerve and, possibly, segmental rhythm generators throughout the medulla that are normally entrained to produce the normal breathing pattern. The data also suggest that the shape of the discharge pattern (augmenting, decrementing) and timing of outputs (alternating vs synchronous) associated with motor outflow during each breath are also dependent on the interconnections between these various sites.     

Sensitivity of basic oscillatory mechanisms for pattern generation and detection

 Intrinsic oscillators are the basic building blocks of central pattern generators, which model the neural circuits underlying pattern generation. Coupled intrinsic oscillators have been shown to synchronize their oscillatory frequencies and to maintain a characteristic pattern of phase relationships. Recently, oscillatory neurons have also been identified in sensory systems that are involved in decoding phase information. It has been hypothesized that the neural oscillators are part of neural circuits that implement phase-locked loops (PLLs), which are well-known electrical circuits for temporal decoding. Thus, there is evidence that intrinsic neural oscillators participate in both temporal pattern generation and temporal pattern decoding. The present paper investigates the dynamics underlying forced oscillators and forced PLLs, using a single framework, and compares both their stability and sensitivity characteristics. In particular, a method for assessing whether an oscillatory neuron is forced directly or indirectly, as part of a PLL, is developed and applied to published data. Received: 17 July 2000 / Accepted in revised form: 14 March 2001