kineoha

• Hanssen, Kine Ødegård; Grødem, Sverre; Fyhn, Marianne; Hafting, Torkel; Einevoll, Gaute & Ness, Torbjørn V [Show all 7 contributors for this article] (2023). Responses in fast-spiking interneuron firing rates to parameter variations associated with degradation of perineuronal nets. Journal of Computational Neuroscience. ISSN 0929-5313. 51, p. 283–298. doi: 10.1007/s10827-023-00849-9. Full text in Research Archive Show summary

  The perineuronal nets (PNNs) are sugar coated protein structures that encapsulate certain neurons in the brain, such as parvalbumin positive (PV) inhibitory neurons. As PNNs are theorized to act as a barrier to ion transport, they may effectively increase the membrane charge-separation distance, thereby affecting the membrane capacitance. Tewari et al. (2018) found that degradation of PNNs induced a 25%-50% increase in membrane capacitance cm and a reduction in the firing rates of PV-cells. In the current work, we explore how changes in cm affects the firing rate in a selection of computational neuron models, ranging in complexity from a single compartment Hodgkin-Huxley model to morphologically detailed PV-neuron models. In all models, an increased cm lead to reduced firing, but the experimentally reported increase in cm was not alone sufficient to explain the experimentally reported reduction in firing rate. We therefore hypothesized that PNN degradation in the experiments affected not only cm, but also ionic reversal potentials and ion channel conductances. In simulations, we explored how various model parameters affected the firing rate of the model neurons, and identified which parameter variations in addition to cm that are most likely candidates for explaining the experimentally reported reduction in firing rate.

• Hanssen, Kine Ødegård & Malthe-Sørenssen, Anders (2022). Perineuronal nets restrict transport near the neuron surface: A coarse-grained molecular dynamics study. Frontiers in Computational Neuroscience. 16. doi: 10.3389/fncom.2022.967735. Full text in Research Archive Show summary

  Perineuronal nets (PNNs) are mesh-like extracellular matrix structures that wrap around certain neurons in the central nervous system. They are hypothesized to stabilize memories in the brain and act as a barrier between cell and extracellular space. As a means to study the impact of PNNs on diffusion, the nets were approximated by negatively charged polymer brushes and simulated by coarse-grained molecular dynamics. Diffusion constants of single neutral and single charged particles were obtained in directions parallel and perpendicular to the brush substrate. The results for the neutral particle were compared to different theories of diffusion in a heuristic manner. Diffusion was found to be considerably reduced for brush spacings smaller than 10 nm, with a pronounced anisotropy for dense brushes. The exact dynamics of the chains was found to have a negligible impact on particle diffusion. The resistance of the brush proved small compared to typical values of the membrane resistance of a neuron, indicating that PNNs likely contribute little to the total resistance of an enwrapped neuron.

• Hanssen, Kine Ødegård; Grødem, Sverre; Fyhn, Marianne; Hafting, Torkel; Einevoll, Gaute & Ness, Torbjørn Vefferstad [Show all 7 contributors for this article] (2022). Effects of perineuronal nets on neural ring properties. Research Square. ISSN 2693-5015. doi: 10.21203/rs.3.rs-2198467/v1. Full text in Research Archive

View all works in NVA