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Intersegmental coordination in the lamprey: Simulations using a network model without segmental boundaries
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.ORCID iD: 0000-0002-0550-0739
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.ORCID iD: 0000-0002-2358-7815
1997 (English)In: Biological Cybernetics, ISSN 0340-1200, E-ISSN 1432-0770, Vol. 76, no 1, 1-9 p.Article in journal (Refereed) Published
Abstract [en]

Swimming in vertebrates such as eel and lamprey involves the coordination of alternating left and right activity in each segment. Forward swimming is achieved by a lag between the onset of activity in consecutive segments rostrocaudally along the spinal cord. The intersegmental phase lag is approximately 1% of the cycle duration per segment and is independent of the swimming frequency. Since the lamprey has approximately 100 spinal segments, at any given time one wave of activity is propagated along the body. Most previous simulations of intersegmental coordination in the lamprey have treated the cord as a chain of coupled oscillators or well-defined segments. Here a network model without segmental boundaries is described which can produce coordinated activity with a phase lag. This 'continuous' pattern-generating network is composed of a column of 420 excitatory interneurons (E1 to E420) and 300 inhibitory interneurons (C1 to C300) on each half of the simulated spinal cord. The interneurons are distributed evenly along the simulated spinal cord, and their connectivity is chosen to reflect the behavior of the intact animal and what is known about the length and strength of the synaptic connections. For example, E100 connects to all interneurons between E51 and E149, but at varying synaptic strengths, while E101 connects to all interneurons between E52 and E150. This unsegmented E-C network generates a motor pattern that is sampled by output elements similar to motoneurons (M cells), which are arranged along the cell column so that they receive input from seven E and five C interneurons. The M cells thus represent the summed excitatory and inhibitory input at different points along the simulated spinal cord and can be regarded as representing the ventral root output to the myotomes along the spinal cord. E and C interneurons have five simulated compartments and Hodgkin-Huxley based dynamics. The simulated network produces rhythmic output over a wide range of frequencies (1-11 Hz) with a phase lag constant over most of the length, with the exception of the 'cut' ends due to reduced synaptic input. As the inhibitory C interneurons in the simulation have more extensive caudal than rostral projections, the output of the simulation has positive phase lags, as occurs in forward swimming. However, unlike the biological network, phase lags in the simulation increase significantly with burst frequency, from 0.5% to 2.3% over the range of frequencies of the simulation. Local rostral or caudal increases in excitatory drive in the simulated network are sufficient to produce motor patterns with increased or decreased phase lags, respectively.

Place, publisher, year, edition, pages
1997. Vol. 76, no 1, 1-9 p.
Keyword [en]
CENTRAL PATTERN GENERATOR, COUPLED NONLINEAR OSCILLATORS, AMINO-ACID RECEPTORS, COMPUTER-BASED MODEL, SPINAL-CORD, FICTIVE LOCOMOTION, NEURAL NETWORKS, REALISTIC SIMULATIONS, MATHEMATICAL-MODELS, MEMBRANE-PROPERTIES
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-13365DOI: 10.1007/s004220050316ISI: A1997WJ06100001OAI: oai:DiVA.org:kth-13365DiVA: diva2:324570
Note
QC 20100615Available from: 2010-06-15 Created: 2010-06-15 Last updated: 2017-12-12Bibliographically approved
In thesis
1. Modeling of bursting mechanisms and coordination in a spinal central pattern generator
Open this publication in new window or tab >>Modeling of bursting mechanisms and coordination in a spinal central pattern generator
1998 (English)Doctoral thesis, comprehensive summary (Other scientific)
Abstract [en]

Mechanisms underlying lotal bursting as well as coordinationbetween different levels of a spinal CPG generating locomotionhave been investigated using computer simulations. A"primitive" jawless vertebrate, the lamprey, is used a.s aprototype model. Most simulations have been conducted using abiophysical neu ron model built on the Hodgkin-Huxley formalismand equipped with Nu+, K+,Ca²+, Kca, LVACa²+ and NMDA activated channels. Inhibitory andexcitatory AMPA/kainate and NMDA synapses are modeled as timedependent conductances with appropriate reversal potentials.For tomparison, Morris-Letar oscillators as well as adaptingleaky integrator-like units are also used.

The basic identified building blocks of the CPG, generatingalternating left right burst activity, tonsist of ipsilaterallyprojecting excitatory neurons (E) and contralaterallyprojecting inhibitory neurons (C). The model neurons are connected in the same way ss has been established experimentally.Sinte several complementary mechanisms may play a role, thepotential of two different neural mechanisms have been exploredwhich can provide burst activity at the segmen tal level, andintersegmental coordination. When alternating left-rightactivity is produced through an escape-like mechanism the quietside is able to become ac tive despite ongoing inhibition fromthe contralateral side. Reciprocal inhibition is then a crucialburst terminating factor. Burst frequency is strongly affectedby the effective inhibition and the drive to escape fromongoing inhibition. Several factors influence this process. Kcacurrents control spike frequency on the active sideand also a post-burst hyperpolarization on the inactive side.Postin hibitory rebound properties, carried by e.g. low voltageactivatedCa²+ currents further can promote escape. Phasicipsilateral excitation and NMDA membrane properties stabilizethe rhythm, especially in the lower frequency range. Severalexperimental observations can be explained based on the effectthese different factors have on effective inhibition andtendency for escape.

Bursting can, however, also be produced by a networkdeprived of inhibition, showing that powerful burst terminatingmechanisms not requiring inhibition exist. In the model withbiophysically detailed neurons such a mechanism could beactivation ofKcacurrents due to accumulation ofCa²+ during the active phase. As shown innon-spiking, as well as biophysically detailed models, aconstant burst proportion over a wide frequency range can beachieved by modulation of the rel ative strength of adaptationin such networks. The left-right inhibition causes left-rightalternation but may not affect the frequency of bursting.

When both types of lotal oscillatory networks are extendedlongitudinally, a rostral to caudal phase delay is producedwhen caudal projections are extended further than the rostralenes. However, the excitatory versus inhibitory projec tionsmay have different roles in the two alternative models. Thisrelative phase delay expressed as % of cycle duration,increases in general with frequency. The simulations suggestthat the conditions at the ends of the simulated chain arecritical for the resulting phase lag. The capability ofbuffering against frequency variations and rapid adjustmentsfollowing perturbations is discussed and com pared with chainsof relaxation oscillators and phase-coupled oscillators.

Place, publisher, year, edition, pages
Stockholm: KTH, 1998. 82 p.
Series
Trita-NA, ISSN 0348-2952 ; 98:10
Keyword
adaptation, central pattern generator, computer simulation, inter segmental coordination, lamprey, locomotion, neural network, rhythmogenesis
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-2673 (URN)91-7170-255-5 (ISBN)
Public defence
1998-06-16, 00:00
Note
QC 20100616Available from: 2000-01-01 Created: 2000-01-01 Last updated: 2010-06-16Bibliographically approved

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