The overall aim of this project is to determine how neuronal activity influences myelination and to what extent myelin plasticity occurs.
The relocation of our Institute and subsequent COVID-19-related restrictions have had a severe negative impact on the progress of this work. Nevertheless, we have made reasonable progress towards our overall aims. Below, I list the main achievements of this programme of work.
1 We found that action potential frequency is important for myelination in vivo. Capitalising on the well-documented development of the Xenopus visual system, we found that myelination varies with the pattern of action potential firing. Developmental myelination is reduced during both low and excessively high stimulation patterns (Chorghay et al., J Comp Neurol. 2022).
2 Based on our findings on how firing patterns differentially regulate myelination, we utilised the myelin regenerative process to uncover some mechanistic insights into how activity influences myelination. Our data indicate that reducing activity during the OPC differentiation period reduces myelination, while increasing it augments myelination. However, if activity is increased during the OPC proliferation period, myelination is reduced (de Faria Jr et al., submitted).
3 We identified that oligodendrocyte precursor cells become heterogeneous with age and differ in properties between brain regions. This heterogeneity alters how these cells respond to neuronal activity (Spitzer, Sitnikov, Kamen et al., Neuron 2019).
4 We found that potassium conductance in OPCs increases with age. Over time, OPCs in all regions acquire high potassium conductance, which may influence regional differences in proliferation. As cells gain high potassium conductance, they enter a dormant state but may potentially reactivate in response to neuronal activity. This dynamic relationship, marked by changes in potassium conductance, is linked to differences in the OPCs' cell cycle state, with high potassium conductance suggesting a G1 phase arrest. These changes may impact how OPCs respond to their environment, potentially altering their role in neural activity (Pivonkova, Sitnikov, Kamen et al., Cell Reports 2024).
5 We have further identified that OPCs have different functional states and can transition between these states. For example, systemic administration of the fasting-mimetic metformin seems to promote the transition of OPCs to a primed state that is sensitive to neuron activity changes (Kamen et al., 2021; Kamen et al., Scientific Reports 2024).
6 We identified that myelination in the cortex continues far into adulthood and differs between cortical layers (de Faria Jr, Nat. Neurosci. 2021; Timmler et al., in preparation for submission).
7 We have set up electroretinogram (ERG) recordings of neuronal activity in retinal ganglion cells, and have recorded a dose-response curve for CNO and clozapine, identifying the dose that provides maximum control of neuronal activity without affecting other aspects of the ERG. Using this dose, we tested the effect of altering neuronal activity in retinal ganglion cells. Using our new mouse models, where we can label either newly formed or existing myelinating cells, we found that myelination is bidirectionally regulated by activity in adults and that neuronal firing rate seems to regulate internodal lengths (Jia, Vagionitis et al., submitted).
8 Reviewing the emerging literature on myelin plasticity and learning we found that collectively, the literature showed that neuronal activity-dependent myelin remodelling may be important for memory consolidation (Bonetto et al., 2021). In recent work we have identified molecules of activity-dependent myelination that are needed for learning evoked myelination programme (in preparation for submission).
9 During the project, we established new methods of analysis and data acquisition focused on artificial intelligence and automated image capture for higher throughput and an unbiased approach.
