| Literature DB >> 32278058 |
Michael E Hasselmo1, Andrew S Alexander2, Alec Hoyland2, Jennifer C Robinson2, Marianne J Bezaire2, G William Chapman2, Ausra Saudargiene2, Lucas C Carstensen2, Holger Dannenberg2.
Abstract
The space of possible neural models is enormous and under-explored. Single cell computational neuroscience models account for a range of dynamical properties of membrane potential, but typically do not address network function. In contrast, most models focused on network function address the dimensions of excitatory weight matrices and firing thresholds without addressing the complexities of metabotropic receptor effects on intrinsic properties. There are many under-explored dimensions of neural parameter space, and the field needs a framework for representing what has been explored and what has not. Possible frameworks include maps of parameter spaces, or efforts to categorize the fundamental elements and molecules of neural circuit function. Here we review dimensions that are under-explored in network models that include the metabotropic modulation of synaptic plasticity and presynaptic inhibition, spike frequency adaptation due to calcium-dependent potassium currents, and afterdepolarization due to calcium-sensitive non-specific cation currents and hyperpolarization activated cation currents. Neuroscience research should more effectively explore possible functional models incorporating under-explored dimensions of neural function.Entities:
Keywords: acetylcholine; biophysical simulations; computational neuroscience; dopamine; neuromodulation; presynaptic inhibition
Mesh:
Year: 2020 PMID: 32278058 PMCID: PMC7541517 DOI: 10.1016/j.neuroscience.2020.03.048
Source DB: PubMed Journal: Neuroscience ISSN: 0306-4522 Impact factor: 3.590