Angela Tuesca
University of Indianapolis
Indianapolis, IN
Faculty Mentor: Dr. James Buchanan

Research has been done in many animals to understand the neuronal basis of locomotor activity. For example, rhythmic stepping can be evoked in spinalized adult cats, and rhythmic motor activity can be elicited in an isolated spinal cord of the neonatal rat preparation by applying an excitatory amino acid. An important conclusion of these types of experiments is that production of the rhythmic movements involved in locomotor activity can be generated by the spinal cord without input from the brain or sensory afferents. Thus, the spinal cord contains a neuronal network for locomotion called a central pattern generator (CPG). In addition to the locomotor CPG, there are CPGs for chewing, scratching, and breathing. Synaptic and cellular properties of neurons within the CPG determine its pattern of output to the motoneurons. The complexity of higher vertebrates makes a simpler model for locomotion advantageous. The isolated spinal cord of the lamprey is such a preparation, having a relatively simple organization, as well as the ability to survive and function in vitro for several days.

Applying an excitatory amino acid, such as D-glutamate, produces swimming activity in the isolated lamprey spinal cord, and this activity is called “fictive swimming”. Higher concentrations of D-glutamate produce higher frequencies of fictive swimming. The frequency of swimming is measured by recording the rhythmic motoneuron (MN) axon spiking in the ventral roots (VRs) using extracellular VR suction electrodes. This rhythmic spiking is caused by regular MN membrane potential oscillations that receive the output of the CPG. The membrane potential oscillations of the MNs have not been characterized at different swim frequencies. If swimming frequency changes, does the MN membrane potential oscillation change as well? These experiments focused on the relationship between the frequency of swimming and the amplitude of the MN membrane potential oscillations. In one set of experiments, different swim frequencies were induced by different concentrations of D-glutamate. In a second set of experiments, swim frequency was altered by adding acetylcholine (ACh), a neuromodulator previously shown to increase swim frequency.

A sharp microelectrode recorded intracellular MN membrane potential oscillations while extracellular suction electrodes positioned on VRs monitored swimming frequency. Each spinal cord preparation was exposed to incremented increases in D-glutamate concentration (0.15 to 1.6 mM). Then in 0.3 mM D-glutamate, the spinal cord was perfused with 0.2 mM ACh. The peak-to-trough amplitude of the MN oscillations and the frequency of VR bursting were measured.

In all six preparations there was no clear relationship between frequency of swimming and MN oscillation amplitude produced with increasing D-glutamate concentration. The maximal peak-to-trough amplitude was achieved at slow frequencies of swimming and remained constant over a range of increasing swim frequencies. In 4/5 preparations, ACh increased the swimming frequency and also decreased the variability in frequency. In all 5 of the ACh preparations the amplitude of the MN oscillations was slightly reduced from the control, but the change was not found to be significant by a t-test.

In conclusion, membrane potential oscillations in MNs do not vary with changes in swimming frequency induced by changes in D-glutamate concentration. Similarly, ACh increased swimming frequency, but did not produce a significant change in MN oscillation amplitude compared to the control. Thus, at the level of the MN membrane potential, the mechanisms of D-glutamate and ACh speeding of the swim CPG do not appear to be significantly different.