Mapping function onto neuronal morphology

作     者：Stiefel, Klaus M. Sejnowski, Terrence J. 

作者机构：Salk Inst Biol Studies Howard Hughes Med Inst Comp Neurol Lab San Diego CA 92138 USA Univ Calif San Diego Dept Biol San Diego CA USA 

出 版 物：《JOURNAL OF NEUROPHYSIOLOGY》 (J. Neurophysiol.)

年 卷 期：2007年第98卷第1期

页      面：513-526页

核心收录：

学科分类：0710[理学-生物学] 1001[医学-基础医学(可授医学、理学学位)] 07[理学] 071003[理学-生理学] 

主　　题：.dendrites optimized Innovative Methodology optimization procedure nucleus laminaris temporal order EPSPs synaptic potentials Neuronal Morphology Function Onto dendritic morphologies computational tasks real neurons linear summation spike-order 

摘      要：Mapping functions onto neuronal morphology. J Neurophysiol 98: 513-526, 2007;doi: 10.1152/jn.00865.2007. Neurons have a wide range of dendritic morphologies the functions of which are largely unknown. We used an optimization procedure to find neuronal morphological structures for two computational tasks: first, neuronal morphologies were selected for linearly summing excitatory synaptic potentials ( EPSPs);second, structures were selected that distinguished the temporal order of EPSPs. The solutions resembled the morphology of real neurons. In particular the neurons optimized for linear summation electrotonically separated their synapses, as found in avian nucleus laminaris neurons, and neurons optimized for spike-order detection had primary dendrites of significantly different diameter, as found in the basal and apical dendrites of cortical pyramidal neurons. This similarity makes an experimentally testable prediction of our theoretical approach, which is that pyramidal neurons can act as spike-order detectors for basal and apical inputs. The automated mapping between neuronal function and structure introduced here could allow a large catalog of computational functions to be built indexed by morphological structure.