Electrotonic architecture of hippocampal CA1 pyramidal neurons based on three-dimensional reconstructions

Abstract

SUMMARYAND CONCLUSIONS1. The spread of electrical signals in pyramidal neurons from the CA1 field of rat hippocampus was investigated through multicompartmental modeling based on three-dimensional morphometric reconstructions of four of these cells. These models were used to dissect the electrotonic architecture of these neurons, and to evaluate the equivalent cylinder approach that this laboratory and others have previously applied to them. Robustness of results was verified by the use of wide ranges of values of specific membrane resistance (R,) and cytoplasmic resistivity.2. The anatomy exhibited extreme departures from a key assumption of the equivalent cylinder model, the so-called "3/2 power law. ' ' 3. The compartmental models showed that the frequency distribution of steady-state electrotonic distances between the soma and the dendritic terminations was multimodal, with a large range and a sizeable coefficient of variation. This violated another central assumption of the equivalent cylinder model, namely, that all terminations are electrotonically equidistant from the soma. This finding, which was observed both for "centrifugal"(away from the soma) and ' 'centripetal" (toward the soma) spread of electrical signals, indicates that the concept of an equivalent electrotonic length for the whole dendritic tree is not appropriate for these neurons.4. The multiple peaks in the electrotonic distance distributions, whether for centrifugal or centripetal voltage transfer, were clearly related to the laminar organization of synaptic afferents in the CA1 region.5. The results in the three preceding paragraphs reveal how little of the electrotonic architecture of these neurons is captured by a simple equivalent cylinder model. The multicompartmental model is more appropriate for exploring synaptic signaling and transient events in CA1 pyramidal neurons.6. There was significant attenuation of synaptic potential, current, and charge as they spread from the dendritic tree to the soma. Charge suffered the least and voltage suffered the most attenuation. Attenuation depended weakly on R, and strongly on synaptic location. Delay of time to peak was more distorted for voltage than for current and was more affected by R,.7. Adequate space clamp is not possible for most of the synapses on these cells. Application of a somatic voltage clamp had no significant effect on voltage transients in the subsynaptic membrane.8. The possible existence of steep voltage gradients within the dendritic tree is consistent with the idea that there can be some degree of local processing and that different regions of the neuron may function semiautonomously. These spatial gradients are potentially relevant to synaptic plasticity in the hippocampus, and they also suggest caution in interpreting some neurophysiological results.

Cell Type- and Subcellular Position-Dependent Summation of Unitary Postsynaptic Potentials in Neocortical Neurons

“…Experiments in brain slices indicated linear input summation in motoneurons (Skydsgaard and Hounsgaard, 1994) and hippocampal pyramidal cells (Langmoen and Andersen, 1983). Physiological tests without the additional information on the subcellular position of inputs leave dendritic integration rules open to several interpretations (Major et al, 1994; Z ador et al, 1995;Mainen et al, 1996). Using local glutamate microiontophoresis and extracellular stimulation onto visualized dendrites, C ash and Yuste (1999) reported linear and position-independent summation of EPSPs.…”

“…The rules of synaptic summation are thought to depend on the dendritic geometry of the postsynaptic cell (Zador et al, 1995;Mainen et al, 1996), on a variety of synaptic-and voltagedependent conductances distributed heterogeneously over the dendritic tree (Johnston et al, 1996;Hausser et al, 2000), and on the relative position and timing of inputs (Jack et al, 1975;Shepherd and Brayton, 1987;Rall et al, 1992;Segev et al, 1995;Hausser et al, 2000). Theoretical analysis of dendritic integration began by assuming that passive cables serve as reasonable models of dendrites (Jack et al, 1975;Segev et al, 1995).…”

Estimation of the physical properties of neurons and glial cells using dielectrophoresis crossover frequency

“…Neuronal physical properties, along with cell interior and membrane electronic structures, have been investigated by various research groups to address cell physiological issues such as membrane voltage response and neuronal synaptic potential integration [1][2][3][4]. Based on a general passive cable model [5], a detailed neuronal electronic structure study was performed with CA1 and CA3 pyramidal neurons, CA3 interneurons and neocortical pyramidal neurons [1-4, 6, 7], where whole-cell patch recording was typically performed for model and property verification.…”

The role of ongoing dendritic oscillations in single-neuron dynamics

“…Yet, the dendritic tree is not a uniform structure. First, morphological properties that are important for the electrical behavior of the dendrite, such as the diameter of the branches, vary throughout the tree (see, for example, [16]). Second, and most importantly for the present report, the distribution of many types of voltage-dependent conductances is typically nonuniform (for review, see [17]).…”