title: Electrophysiological classification of somatostatin-positive interneurons in mouse sensorimotor cortex.
abstract: Classification of inhibitory interneurons is critical in determining their role in normal information processing and pathophysiological conditions such as epilepsy. Classification schemes have relied on morphological, physiological, biochemical, and molecular criteria; and clear correlations have been demonstrated between firing patterns and cellular markers such as neuropeptides and calcium-binding proteins. This molecular diversity has allowed generation of transgenic mouse strains in which GFP expression is linked to the expression of one of these markers and presumably a single subtype of neuron. In the GIN mouse (EGFP-expressing Inhibitory Neurons), a subpopulation of somatostatin-containing interneurons in the hippocampus and neocortex is labeled with enhanced green fluorescent protein (EGFP). To optimize the use of the GIN mouse, it is critical to know whether the population of somatostatin-EGFP-expressing interneurons is homogeneous. We performed unsupervised cluster analysis on 46 EGFP-expressing interneurons, based on data obtained from whole cell patch-clamp recordings. Cells were classified according to a number of electrophysiological variables related to spontaneous excitatory postsynaptic currents (sEPSCs), firing behavior, and intrinsic membrane properties. EGFP-expressing interneurons were heterogeneous and at least four subgroups could be distinguished. In addition, multiple discriminant analysis was applied to data collected during whole cell recordings to develop an algorithm for predicting the group membership of newly encountered EGFP-expressing interneurons. Our data are consistent with a heterogeneous population of neurons based on electrophysiological properties and indicate that EGFP expression in the GIN mouse is not restricted to a single class of somatostatin-positive interneuron.
authors.affiliation: Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94305-5122, USA.
authors.forename: Brian
authors.initials: B
authors.lastname: Halabisky
authors.forename: Fran
authors.initials: F
authors.lastname: Shen
authors.forename: John R
authors.initials: JR
authors.lastname: Huguenard
authors.forename: David A
authors.initials: DA
authors.lastname: Prince
mesh_terms: D000465:Algorithms; D000818:Animals; D002452:Cell Count; D016000:Cluster Analysis; D004558:Electric Stimulation; D004594:Electrophysiology; D019706:Excitatory Postsynaptic Potentials / Q000502:physiology; D049452:Green Fluorescent Proteins / Q000378:metabolism; D007150:Immunohistochemistry; D066298:In Vitro Techniques; D007395:Interneurons / Q000145:classification* / Q000502:physiology*; D051379:Mice; D008959:Models, Neurological; D009044:Motor Cortex / Q000166:cytology / Q000502:physiology*; D019579:Neocortex / Q000502:physiology; D018408:Patch-Clamp Techniques; D013003:Somatosensory Cortex / Q000166:cytology / Q000502:physiology*; D013004:Somatostatin / Q000502:physiology*
chemical_list: D049452:Green Fluorescent Proteins; D013004:Somatostatin