title: Modeling intracellular signaling underlying striatal function in health and disease.
abstract: Striatum, which is the input nucleus of the basal ganglia, integrates cortical and thalamic glutamatergic inputs with dopaminergic afferents from the substantia nigra pars compacta. The combination of dopamine and glutamate strongly modulates molecular and cellular properties of striatal neurons and the strength of corticostriatal synapses. These actions are performed via intracellular signaling networks, containing several intertwined feedback loops. Understanding the role of dopamine and other neuromodulators requires the development of quantitative dynamical models for describing the intracellular signaling, in order to provide precise unambiguous descriptions and quantitative predictions. Building such models requires integration of data from multiple data sources containing information regarding the molecular interactions, the strength of these interactions, and the subcellular localization of the molecules. Due to the uncertainty, variability, and sparseness of these data, parameter estimation techniques are critical for inferring or constraining the unknown parameters, and sensitivity analysis evaluates which parameters are most critical for a given observed macroscopic behavior. Here, we briefly review the modeling approaches and tools that have been used to investigate biochemical signaling in the striatum, along with some of the models built around striatum. We also suggest a future direction for the development of such models from the, now becoming abundant, high-throughput data.
authors.affiliation: School of Computer Science and Communication, Royal Institute of Technology, Stockholm, Sweden.
authors.forename: Anu G
authors.initials: AG
authors.lastname: Nair
authors.affiliation: School of Computer Science and Communication, Royal Institute of Technology, Stockholm, Sweden.
authors.forename: Omar
authors.initials: O
authors.lastname: Gutierrez-Arenas
authors.affiliation: Department of Numerical Analysis and Computer Science, Stockholm University, Stockholm, Sweden.
authors.forename: Olivia
authors.initials: O
authors.lastname: Eriksson
authors.affiliation: Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
authors.forename: Alexandra
authors.initials: A
authors.lastname: Jauhiainen
authors.affiliation: Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA, USA.
authors.forename: Kim T
authors.initials: KT
authors.lastname: Blackwell
authors.affiliation: School of Computer Science and Communication, Royal Institute of Technology, Stockholm, Sweden; Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden.
authors.forename: Jeanette H
authors.initials: JH
authors.lastname: Kotaleski
mesh_terms: D006262:Health; D006801:Humans; D042541:Intracellular Space / Q000378:metabolism*; D008959:Models, Neurological; D009422:Nervous System Diseases / Q000378:metabolism* / Q000473:pathology*; D015398:Signal Transduction; D013223:Statistics as Topic
keywords: DARPP32; Dopamine; Kinetic models; LTP; Medium spiny neurons; Neural data integration; Postsynaptic signaling; Striatum; Synaptic plasticity