Biomedical subjects

T Kiemel

Publications and source records attributed to T Kiemel.

8 recordsLinked to original sources

PubMed1996

Interaction between the caudal brainstem and the lamprey central pattern generator for locomotion.

Because of its remarkable simplicity and the robustness of the isolated preparation, the lamprey has been used as a model system to study locomotion and its central pattern generator. The function of the spinal cord is relatively well understood in this context, but the role of the brain or even the caudal brainstem remains less so. We here present a study of the interaction between the caudal brainstem and the spinal pattern generator for locomotion. We show that the interaction is highly complex, with both feedforward input from the brainstem to spinal cord and feedback input from the spinal cord to brainstem playing a significant role in the motor output during locomotion. The brainstem, when diffusely stimulated pharmacologically, can initiate fictive locomotion, or it can disrupt or alter the ongoing D-glutamate initiated motor output. The nature of the disruptions vary greatly, and can induce generalized irregularity, while the alterations can include accelerating or decelerating of the bursting. All behaviors are displayed with spectrograms of the motor nerve discharge. We also show that the unstimulated brainstem can disrupt as well as slow the bursting, but in a complex fashion. Finally, a slow episodic behavior initiated from the caudal brainstem is also described. This can be elicited either by D-glutamate to the brainstem or by ascending activity from the spinal cord pattern generator. Thus, we demonstrate that the interaction between the brainstem and the spinal cord during the production of locomotion is highly complex. The locomotion that is exhibited by the combined brainstem-spinal cord preparation is extremely variable. This is in striking contrast to the variability of the locomotor output pharmacologically induced in the spinal cord alone. The latter preparation exhibits remarkable regularity, or upon occasion, irregularity, but not the routine irregularity or the systemic up and down changes in frequency seen with the brainstem present. However, the pattern of frequency changes induced by the brainstem is not predictable, and remains to be understood.

Animals↗

PubMed1996

Dynamic behavior of a neural network model of locomotor control in the lamprey.

1. Experimental studies have shown that a central pattern generator in the spinal cord of the lamprey can produce the basic rhythm for locomotion. This pattern generator interacts with the reticular neurons forming a spinoreticulospinal loop. To better understand and investigate the mechanisms for locomotor pattern generation in the lamprey, we examine the dynamic behavior of a simplified neural network model representing a unit spinal pattern generator (uPG) and its interaction with the reticular system. We use the techniques of bifurcation analysis and specifically examine the effects on the dynamic behavior of the system of 1) changing tonic drives to the different neurons of the uPG; 2) altering inhibitory and excitatory interconnection strengths among the uPG neurons; and 3) feedforward-feedback interactions between the uPG and the reticular neurons. 2. The model analyzed is a qualitative left-right symmetric network based on proposed functional architecture with one class of phasic reticular neurons and three classes of uPG neurons: excitatory (E), lateral (L), and crossed (C) interneurons. In the model each class is represented by one left and one right neuron. Each neuron has basic passive properties akin to biophysical neurons and receives tonic synaptic drive and weighted synaptic input from other connecting neurons. The neuron's output as a function of voltage is given by a nonlinear function with a strict threshold and saturation. 3. With an appropriate set of parameter values, the voltage of each neuron can oscillate periodically with phase relationships among the different neurons that are qualitatively similar to those observed experimentally. The uPG alone can also oscillate, as observed experimentally in isolated lamprey spinal cords. Varying the parameters can, however, profoundly change the state of the system via different kinds of bifurcations. Change in a single parameter can move the system from nonoscillatory to oscillatory states via different kinds of bifurcations. For some parameter values the system can also exhibit multistable behavior (e.g., an oscillatory state and a nonoscillatory state). The analysis also shows us how the amplitudes of the oscillations vary and the periods of limit cycles change as different bifurcation points are approached. 4. Altering tonic drive to just one class of uPG neurons (without altering the interconnections) can change the state of the system by altering the stability of fixed points, converting fixed points to oscillations, single oscillations to two stable oscillations, etc. Two-parameter bifurcation diagrams show the critical regions in which a balance between the tonic drives is necessary to maintain stable oscillations. A minimum tonic drive is necessary to obtain stable oscillatory output. With appropriate changes in the tonic drives to the L and C neurons, stable oscillatory output can be obtained even after eliminating the E neurons. Indeed, the presence of active E neurons in the biological system does not prove they play a functional role in the system, because tonic drive from other sources can substitute for them. On the other hand, very high excitation of any one class of neurons can terminate oscillations. Appropriate balance of tonic drives to different neuron classes can help sustain stable oscillations for larger tonic drives. Published experimental results concerning changes in amplitude and swimming frequency with increased tonic drives are mimicked by the model's responses to increased tonic drive. 5. Interconnectivity among the neurons plays a crucial role. The analysis indicates that the C and L classes of neurons are essential components of the model network. Sufficient inhibition from the L to C neurons as well as mutual inhibition between the left and right halves is necessary to obtain stable oscillatory output. When the E neurons are present in the model network, they must receive appropriate tonic drive and provide appropriate excitation

Animals↗

PubMed1995

Topological and phenomenological classification of bursting oscillations.

We describe a classification scheme for bursting oscillations which encompasses many of those found in the literature on bursting in excitable media. This is an extension of the scheme of Rinzel (in Mathematical Topics in Population Biology, Springer, Berlin, 1987), put in the context of a sequence of horizontal cuts through a two-parameter bifurcation diagram. We use this to describe the phenomenological character of different types of bursting, addressing the issue of how well the bursting can be characterized given the limited amount of information often available in experimental settings.

Animals↗

PubMed1995

Correlational analysis of fictive swimming in the lamprey reveals strong functional intersegmental coupling.

1. Cycle-to-cycle fluctuations in cycle periods and intersegmental burst delays of ventral root activity were studied during stable fictive swimming in the adult lamprey spinal cord. High spatial resolution was obtained by recording from 16 ventral roots, 1/2 on each side of the spinal cord. For ipsilateral ventral roots, correlations between cycle periods on the same cycle were high (0.50 +/- 0.16, mean +/- SD), and autocorrelations of intersegmental delays with a shift of one cycle were low (0.03 +/- 0.06). Correlations between cycle periods tended to decrease with intersegmental spacing but remained positive over the range of spacings tested (1-47 segments). 2. Sinusoidal movement imposed on the caudal end of the spinal cord/notochord was used to entrain the fictive swimming rhythm. When the phase between the movement and the rhythm was perturbed, several cycles were required for the phase to return to its preferred value, indicating that in these experiments the effect of the movement was weak. In the absence of external perturbations, autocorrelations of delays between the movement and ventral root bursts with a shift of one cycle were high. 3. Numerical simulations with a simple stochastic phase model of the lamprey central pattern generator (CPG) were conducted. High correlations of periods and low autocorrelations of delays, the pattern observed experimentally, emerged as intersegmental connection strengths were increased. Coupling including both long and short connections produced this pattern of correlations with an average connection strength less than that required by short connections alone. 4. It is concluded that functional intersegmental coupling in the lamprey CPG during stable fictive swimming is strong. Specifically, the low autocorrelations of intersegmental delays indicate that intersegmental coupling is sufficiently strong to ensure that perturbations are almost completely corrected within one cycle.

Animals↗

PubMed1993

Pattern switching in human multilimb coordination dynamics.

A relative phase model of four coupled oscillators is used to interpret experiments on the coordination between rhythmically moving human limbs. The pairwise coupling functions in the model are motivated by experiments on two-limb coordination. Stable patterns of coordination between the limbs are represented by fixed points in relative phase coordinates. Four invariant circles exist in the model, each containing two patterns of coordination seen experimentally. The direction of switches between two four-limb patterns on the same circle can be understood in terms of two-limb coordination. Transitions between patterns in the human four-limb system are theoretically interpreted as bifurcations in a nonlinear dynamical system.

Animals↗

PubMed1992

Modelling of intersegmental coordination in the lamprey central pattern generator for locomotion.

Rhythmic motor activity requires coordination of different muscles or muscle groups so that they are all active with the same cycle duration and appropriate phase relationships. The neural mechanisms for such phase coupling in vertebrate locomotion are not known. Swimming in the lamprey is accomplished by the generation of a travelling wave of body curvature in which the phase coupling between segments is so controlled as to give approximately one full wavelength on the body at any swimming speed. This article reviews work that has combined mathematical analysis, biological experimentation and computer simulation to provide a conceptual framework within which intersegmental coordination can be investigated. Evidence is provided to suggest that in the lamprey, ascending coupling is dominant over descending coupling and controls the intersegmental phase lag during locomotion. The significance of long-range intersegmental coupling is also discussed.

Animals↗

PubMed1990

The development of the lamprey pattern generator for locomotion.

The life cycle of the lamprey includes a larval stage that can last for several years. The motor behavior of the larval lamprey, the ammocoete, has been only minimally studied and little is known of the neural correlates of that behavior. Comparison of known larval behavior to that of adults leaves unclear whether there are large or small changes in the spinal nervous system during transformation. The motor output of isolated larval and transforming spinal cords when stimulated to "swim" with D-glutamate has some differences from that of comparable adult preparations, but shares many important features with adults. Primarily, the fictive swimming is less well regulated and less stable than adults of the same species. We propose that a major difference in the structure and organization of the central pattern generator for locomotion between adults and ammocoetes is a relative lack or immaturity of some cell types that participate in the coordination of the segments and the generation of the rhythm of the periodic bursting.

Animals↗

PubMed1987

A model for the periodic synaptic inhibition of a neuronal oscillator.

We develop a simple, piecewise linear differential equation with discontinuous jumps, which captures the essential characteristics of more complicated equations modelling the dynamics of neuronal oscillators, such as those due to Hodgkin & Huxley (1952), Fitzhugh (1960, 1961), and Nagumo et al. (1962). We investigate the effects of periodically applied stimuli of various durations and compare phase-transition curves or Poincaré maps for our model with numerically computed maps from the 'full' equations. We describe some aspects of the qualitative behaviour and bifurcations of these iterated one-dimensional mappings and attempt to relate them to experimental observations.

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