Abstract

In vivo and in vitro multichannel field and somatic intracellular recordings are frequently used to study mechanisms of network pattern generation. When interpreting these data, neurons are often implicitly considered as electrotonically compact cylinders with a homogeneous distribution of excitatory and inhibitory inputs. However, the actual distributions of dendritic length, diameter, and the densities of excitatory and inhibitory input are non-uniform and cell type-specific. We first review quantitative data on the dendritic structure and synaptic input and output distribution of pyramidal cells (PCs) and interneurons in the hippocampal CA1 area. Second, using multicompartmental passive models of four different types of neurons, we quantitatively explore the effect of differences in dendritic structure and synaptic distribution on the errors and biases of voltage clamp measurements of inhibitory and excitatory postsynaptic currents. Finally, using the 3-dimensional distribution of dendrites and synaptic inputs we calculate how different inhibitory and excitatory inputs contribute to the generation of local field potential in the hippocampus. We analyze these effects at different realistic background activity levels as synaptic bombardment influences neuronal conductance and thus the propagation of signals in the dendritic tree. We conclude that, since dendrites are electrotonically long and entangled in 3D, somatic intracellular and field potential recordings miss the majority of dendritic events in some cell types, and thus overemphasize the importance of perisomatic inhibitory inputs and belittle the importance of complex dendritic processing. Modeling results also suggest that PCs and inhibitory neurons probably use different input integration strategies. In PCs, second- and higher-order thin dendrites are relatively well-isolated from each other, which may support branch-specific local processing as suggested by studies of active dendritic integration. In the electrotonically compact parvalbumin- and cholecystokinincontaining interneurons, synaptic events are visible in the whole dendritic arbor, and thus the entire dendritic tree may form a single integrative element. Calretinin-containing interneurons were found to be electrotonically extended, which suggests the possibility of complex dendritic processing in this cell type. Our results also highlight the need for the integration of methods that allow the measurement of dendritic processes into studies of synaptic interactions and dynamics in neural networks.

Highlights

  • Our image of neurons and their integrative processes grows ever more complex thanks to significant improvements in technology

  • The distribution of excitatory and inhibitory synaptic inputs over key populations of rat hippocampal CA1 area neurons: pyramidal cells (PCs), PV, CCK, Calbindin D28k, and CR-positive as well as two types of hippocamposeptally projecting (HS) inhibitory neuron (IN) has been quantitatively described (Gulyás et al, 1999; Megías et al, 2001; Mátyás et al, 2004; Takács et al, 2008)

  • Experimental studies have shown that somatic and proximal dendritic intracellular recordings in pyramidal neurons miss a significant portion of synaptic inputs, save the perisomatic ones, especially at physiological levels of network activity (Williams and Mitchell, 2008; Marchionni and Maccaferri, 2009)

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Summary

Introduction

Our image of neurons and their integrative processes grows ever more complex thanks to significant improvements in technology. A set of studies examined the interactions of specific cell types in cortical networks, with the aim of understanding the generation of different kinds of population dynamics such as coherent oscillations and transient synchrony (Butler and Paulsen, 2015; Gulyás and Freund, 2015) These studies employed somatic patch-clamp recordings and extracellular electrode arrays in vivo and in vitro (Ylinen et al, 1995; Lakatos et al, 2005; Mann et al, 2005; Oren et al, 2006, 2010; Montgomery et al, 2009; Makarov et al, 2010; Sullivan et al, 2011; Scheffer-Teixeira et al, 2012, 2013), which allow recording from all layers of a structure and the calculation of currents flowing in and out of neurons during different activity patterns. Several recent papers, using complex recording methods and data analysis, dissected how the activity of different identified cell types (Mann et al, 2005; Oren et al, 2006, 2010; Hájos et al, 2013) and input pathways (Isomura et al, 2006; Montgomery et al, 2009) contribute to the generation of network activity, and how excitatory and inhibitory synaptic currents and voltage-gated currents shape neuronal activity and field potentials (Buzsáki et al, 2012)

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