CRCNS: Understanding Single-Neuron Computation Using Nonlinear Model Optimization

Baylor College Of Medicine, Houston TX

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Abstract

Project Description 1 Motivation and Objectives Why are ion channels localized in subcellular dendritic compartments and is there a tight coupling of the observed localization with neuron function? We argue that this fundamental question [55, 44] can be addressed by studying the biophysical mechanisms of single neuron computation in two model systems where a large amount of electrophysiological and anatomical data is available and has been tied to the functional roles of key neurons. The neurons selected, CA1 hippocampal pyramidal cells and the lobula giant movement detector (LGMD) neuron of grasshoppers, are ideal because we know precisely their role in the emergence of place fields and collision detection, respectively. Furthermore, the involved dendritic ion channels are closely related and can be studied jointly using the common language of compartmental modeling and the Hodgkin-Huxley formalism [97, 56]. Complementarity will allow to draw broader conclusions than by studying either system in isolation. 1.1 Channel Localization and Single Neuron Computation Abundant evidence suggests that ion channels are precisely localized within single neurons. Yet the role of this localization for neuronal information processing remains largely unexplored. The best-known example of zonal channel localization is the axon initial segment, where high densities of Na+ and K+ channels over a short distance play a pivotal role in the generation of action potentials [64]. In dendrites, a variety of conductances are localized in specific dendritic subregions, with densities that often depend on the distance from the spike initiation zone (SIZ) [77, 72]. Channel localization has been studied in specific neuron types such as pyramidal cells of the hip- pocampus and neocortex in rodents through in vitro patch-clamp recordings along the main apical den- drite. These recordings show the presence of Na+ channels that help relay synaptic inputs towards the soma and help action potentials backpropagate in dendrites [99, 66]. Additionally, Ca2+ channel ‘hot spots’ help trigger dendritic spikes favoring non-linear amplification of localized synaptic inputs in layer 5 (L5) neocortical pyramidal cells [63, 73]. In several types of neurons, an increase in HCN channel density away from the SIZ favors consistent synaptic summation across the dendritic tree [71]. Further, a concomitant increase in the density of inactivating K+ channels helps fine tune the role of HCN chan- nels during synaptic integration in hippocampal pyramidal cells [21]. These results have been confirmed through simulations, but their significance for information processing remains elusive. The spatial distribution of channels within dendrites has also been investigated using immunostaining, a method that reveals the localization of ion channels but that is not always in quantitative agreement with electrophysiological methods [67, 70, 40]. In Drosophila, novel methods allows visualization of Na+ channel distributions based on genetically encoded fluorescent markers [90], but the function of ion channels for information processing in single neurons is only beginning to be studied. In the few examples highlighted above, we know little about how constrained ion channel distributions are. This issue has been investigated in the stomatogastric system (STG) of crabs, where a small network of identified neurons generates rhythmic membrane potential oscillations involved in various phases of digestion. In STG neurons, substantial variability in ion channel expression levels has been observed [68, 95, 22]. Simulations confirmed that there exists a large redundancy in neuronal peak conductance levels explaining the STG’s rhythmic behavior [89]. These simulations used point-model neurons lacking dendrites and thus did not address the specificity of dendritic ion channel localization. Thus, little is currently known on the contribution of subcellular ion channel localization to single neuron computation. 1.2 CA1 Pyramidal Cells and Place Fields Behavioral timescale synaptic plasticity (BTSP) was recently reported to underlie the formation of place fields in CA1 pyramidal cells of rodents during spatial exploration of an environment [16]. This plasticity 33