title: Analysis of neural coding through quantization with an information-based distortion measure.
abstract: We discuss an analytical approach through which the neural symbols and corresponding stimulus space of a neuron or neural ensemble can be discovered simultaneously and quantitatively, making few assumptions about the nature of the code or relevant features. The basis for this approach is to conceptualize a neural coding scheme as a collection of stimulus-response classes akin to a dictionary or 'codebook', with each class corresponding to a spike pattern 'codeword' and its corresponding stimulus feature in the codebook. The neural codebook is derived by quantizing the neural responses into a small reproduction set, and optimizing the quantization to minimize an information-based distortion function. We apply this approach to the analysis of coding in sensory interneurons of a simple invertebrate sensory system. For a simple sensory characteristic (tuning curve), we demonstrate a case for which the classical definition of tuning does not describe adequately the performance of the cell studied. Considering a more involved sensory operation (sensory discrimination), we also show that, for some cells in this system, a significant amount of information is encoded in patterns of spikes that would not be discovered through analyses based on linear stimulus-response measures.
authors.affiliation: Center for Computational Biology, Montana State University, Bozeman, MT 59717, USA.
authors.forename: Alexander G
authors.initials: AG
authors.lastname: Dimitrov
authors.forename: John P
authors.initials: JP
authors.lastname: Miller
authors.forename: Tomás
authors.initials: T
authors.lastname: Gedeon
authors.forename: Zane
authors.initials: Z
authors.lastname: Aldworth
authors.forename: Albert E
authors.initials: AE
authors.lastname: Parker
mesh_terms: D000388:Air; D000465:Algorithms; D000818:Animals; D005260:Female; D017952:Ganglia, Invertebrate / Q000502:physiology; D006135:Gryllidae; D066298:In Vitro Techniques; D007257:Information Theory; D008564:Membrane Potentials / Q000502:physiology; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D016011:Normal Distribution; D010469:Perceptual Distortion / Q000502:physiology*; D010812:Physical Stimulation; D011930:Reaction Time; D012677:Sensation / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted