Abstract of Zador, Agmon-Snir and Segev, 1995
Zador, A., Agmon-Snir, H., and Segev, I. 1995. The
morphoelectrotonic transform: a graphical approach to dendritic function. J.
Neuroscience 15: 1669-1682.
Electrotonic structure of dendrites plays a critical role in neuronal
computational and plasticity. In this paper we develop two novel measures of
electrotonic structure that describe intraneuronal signaling in dendrites of
arbitrary geometry. The log-attenuation L_ij measures the efficacy, and the
propagation delay P_ij the speed, of signal transfer between any two points i
and j. These measures are additive, in the sense that if j lies between i and
k, the total distance L_ik is just the sum of the partial distances: L_ik =
L_ij + L_jk, and similarly P_ik = P_ij + P_jk. This property serves as the
basis for the morphoelectrotonic transform (MET), a graphical mapping from
morphological into electrotonic space. In a MET, either P_ij or L_ij replace
anatomical distance as the fundamental unit and so provide direct functional
measures of intraneuronal signaling. The analysis holds for arbitrary transient
signals, even those generated by nonlinear conductance changes underlying both
synaptic and action potentials. Depending on input location and the measure of
interest, a single neuron admits many METs, each emphasizing different
functional consequences of the dendritic electrotonic structure. Using a
single layer 5 cortical pyramidal, we illustrate a collection of METs that lead
to a deeper understanding of the electrical behavior of its dendritic tree. We
then compare this cortical cell to representative neurons from other brain
regions (cortical layer 2/3 pyramidal, region CA1 hippocampal pyramidal, and
cerebellar Purkinje). Finally, we apply the MET to electrical signaling in
dendritic spines, and extend this analysis to calcium signaling within spines.
Our results demonstrate that the MET provides a powerful tool for obtaining a
rapid and intuitive grasp of the functional properties of dendritic trees.
Tony Zador can be reached at
zador@salk.edu. Idan Segev can reached at
idan@hujivms.huji.ac.il. Hagai Agmon-Snir can reached at
hagai@helix.nih.gov.
Another way for analyzing the morphoelectrotonic transform
is by using The Electrotonic Workbench.
This set of software tools, developed by N.T. Carnevale, K.Y. Tsai and M.L. Hines, analyzes
the electrotonic architecture of neurons using
NEURON.
hagai@helix.nih.gov