INTERSEGMENTAL COORDINATION IN THE LAMPREY - SIMULATIONS USING A NETWORK MODEL WITHOUT SEGMENTAL BOUNDARIES

Swimming in vertebrates such as eel and lamprey involves the coordinat ion of alternating left and right activity in each segment. Forward sw imming is achieved by a lag between the onset of activity in consecuti ve segments rostrocaudally along the spinal cord. The intersegmental p hase lag is approximately 1% of the cycle duration per segment and is independent of the swimming frequency. Since the lamprey has approxima tely 100 spinal segments, at any given time one wave of activity is pr opagated along the body. Most previous simulations of intersegmental c oordination in the lamprey have treated the cord as a chain of coupled oscillators or well-defined segments. Here a network model without se gmental boundaries is described which can produce coordinated activity with a phase lag. This 'continuous' pattern-generating network is com posed of a column of 420 excitatory interneurons (E1 to E420) and 300 inhibitory interneurons (C1 to C300) on each half of the simulated spi nal 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 o f the synaptic connections. For example, E100 connects to all interneu rons between E51 and E149, but at varying synaptic strengths, while E1 01 connects to all interneurons between E52 and E150. This unsegmented E-C network generates a motor pattern that is sampled by output eleme nts similar to motoneurons (M cells), which are arranged along the cel l column so that they receive input from seven E and five C interneuro ns. The M cells thus represent the summed excitatory and inhibitory in put at different points along the simulated spinal cord and can be reg arded as representing the ventral root output to the myotomes along th e spinal cord. E and C interneurons have five simulated compartments a nd Hodgkin-Huxley based dynamics. The simulated network produces rhyth mic 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' end s due to reduced synaptic input. As the inhibitory C interneurons in t he simulation have more extensive caudal than rostral projections, the output of the simulation has positive phase lags, as occurs in forwar d 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 suff icient to produce motor patterns with increased or decreased phase lag s, respectively.