The Unexplored Territory of Neural Models: Potential Guides for Exploring the Function of Metabotropic Neuromodulation
| Autor: | Michael E. Hasselmo, Marianne Bezaire, G. William Chapman, Lucas C. Carstensen, Alec Hoyland, Ausra Saudargiene, Jennifer C. Robinson, Holger Dannenberg, Andrew S. Alexander |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
Computational neuroscience Neuronal Plasticity Quantitative Biology::Neurons and Cognition Computer science General Neuroscience Models Neurological Action Potentials Function (mathematics) Parameter space Neuromodulation (medicine) Article Membrane Potentials 03 medical and health sciences Range (mathematics) 030104 developmental biology 0302 clinical medicine Metabotropic receptor Synaptic plasticity Neuroscience 030217 neurology & neurosurgery Network model |
| Zdroj: | Neuroscience |
| ISSN: | 1873-7544 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect