In biological networks, millions of neurons organize themselves from microscopic noisy individuals to robust macroscopic entities. These entities are capable of producing higher functions like sensory processing, decision-making, and elaborate behavioral responses. Every aspect of these behaviors is the outcome of an advanced orchestration of the activity of populations of neurons. Through spiking activity, neurons are able to interact; yet we know little about how this interaction occurs in spinal networks. How is the activity distributed across the population? What is the composition of synaptic input that is received by the individual neurons and how is the synaptic input processed? This thesis focuses on aspects of these questions for spinal networks involved in the generation of stereotypical motor behaviors.
The thesis consists of two studies. In the first study, I investigated the synaptic input to motoneurons during rhythmic motor behaviors, and specifically the hypothesis that motoneurons receive concurrent excitatory and inhibitory (E/I) inputs. Berg et al. (2007) presented the concurrent hypothesis, which goes against the classical feed forward reciprocal model for spinal motor networks that has gained widespread acceptance. We developed an adult turtle preparation where the spinal motor network was intact, which also allowed us to perform intracellular recordings from motoneurons during rhythmic motor activity. We estimated the synaptic excitatory and inhibitory conductances by two individual methods. We found that the synaptic input to motoneurons primarily consisted of concurrent exci- tation and inhibition. We quantified the similarities found in intracellular recordings from the intact preparation with a transected turtle preparation, which was missing part of the spinal network. The transected preparation was used in Berg et al. (2007). We found no significant difference between the intracellular recordings from motoneurons performed in the two preparations. A spinal transection had marginal effects on the network integrity and the synaptic fluctuations were unaltered. We imple- mented a balanced network model that is widely applicable to data from cortex, to explain our results from the spinal cord. We found that this network was highly resilient to structural division. Both the experimental findings and the network model support that motoneurons receive concurrent synaptic E/I during behaviors from a premotor network with recurrent connections, which is operating in the irregular regime.
Our experimental findings are in agreement with studies from the cortex and the balanced model. It is therefore relevant to study the population activity in the spinal cord for traits from cortex studies. In the second study, we looked into the distribution of firing rates during different motor programs and the mechanisms that give rise to the distribution. We implanted high-density silicon probes in the spinal cord and recorded parallel single unit activity while inducing different scratch behaviors. We find that neuronal populations in the spinal cord have highly skewed distributions of firing rates. The majority of the neurons was spiking at low firing rates, while a minority had an activity level that was much higher. The distribution is lognormal-like and robust across trials, and it remains skewed in different behaviors. Our findings support that the neuronal activity, which is involved in motor behavior, is governed by synaptic fluctuations and as a result thereof is irregular. Similar lognormal- like distributions of firing rates have also been observed in other brain areas (Buzsáki and Mizuseki, 2014). Roxin et al. (2011) detailed the firing rate distribution in networks in the balanced regime, and found it to be similar to a lognormal distribution and describing the data from the population studies very well.
Our experimental observations and analysis are in agreement with the balanced model proposed by van Vreeswijk and Sompolinsky (1996) and Roxin et al. (2011). The studied spinal neuronal network is predominantly operating in the irregular subthreshold regime, yet neurons are pushed towards the regular superthreshold regime with increased synaptic input.