Axonal morphometry of hippocampal pyramidal neurons semi-automatically reconstructed after in vivo labeling in different CA3 locations.

Axonal arbors of principal neurons form the backbone of neuronal networks in the mammalian cortex. Three-dimensional reconstructions of complete axonal trees are invaluable for quantitative analysis and modeling. However, digital data are still sparse due to labor intensity of reconstructing these complex structures. We augmented conventional tracing techniques with computational approaches to reconstruct fully labeled axonal morphologies. We digitized the axons of three rat hippocampal pyramidal cells intracellularly filled in vivo from different CA3 sub-regions: two from areas CA3b and CA3c, respectively, toward the septal pole, and one from the posterior/ventral area (CA3pv) near the temporal pole. The reconstruction system was validated by comparing the morphology of the CA3c neuron with that traced from the same cell by a different operator on a standard commercial setup. Morphometric analysis revealed substantial differences among neurons. Total length ranged from 200 (CA3b) to 500 mm (CA3c), and axonal branching complexity peaked between 1 (CA3b and CA3pv) and 2 mm (CA3c) of Euclidean distance from the soma. Length distribution was analyzed among sub-regions (CA3a,b,c and CA1a,b,c), cytoarchitectonic layers, and longitudinal extent within a three-dimensional template of the rat hippocampus. The CA3b axon extended thrice more collaterals within CA3 than into CA1. On the contrary, the CA3c projection was double into CA1 than within CA3. Moreover, the CA3b axon extension was equal between strata oriens and radiatum, while the CA3c axon displayed an oriens/radiatum ratio of 1:6. The axonal distribution of the CA3pv neuron was intermediate between those of the CA3b and CA3c neurons both relative to sub-regions and layers, with uniform collateral presence across CA3/CA1 and moderate preponderance of radiatum over oriens. In contrast with the dramatic sub-region and layer differences, the axon longitudinal spread around the soma was similar for the three neurons. To fully characterize the axonal diversity of CA3 principal neurons will require higher-throughput reconstruction systems beyond the threefold speed-up of the method adopted here.

Self-sustaining non-repetitive activity in a large scale neuronal-level model of the hippocampal circuit.

The mammalian hippocampus is involved in spatial representation and memory storage and retrieval, and much research is ongoing to elucidate the cellular and system-level mechanisms underlying these cognitive functions. Modeling may be useful to link network-level activity patterns to the relevant features of hippocampal anatomy and electrophysiology. Investigating the effects of circuit connectivity requires simulations of a number of neurons close to real scale. To this end, we construct a model of the hippocampus with 16 distinct neuronal classes (including both local and projection cells) and 200,000 individual neurons. The number of neurons in each class and their interconnectivity are drawn from rat anatomy. Here we analyze the emergent network activity and how it is affected by reducing either the size or the connectivity diversity of the model. When the model is run with a simple variation of the McCulloch-Pitts formalism, self-sustaining non-repetitive activity patterns consistently emerge. Specific firing threshold values are narrowly constrained for each cell class upon multiple runs with different stochastic wiring and initial conditions, yet these values do not directly affect network stability. Analysis of the model at different network sizes demonstrates that a scale reduction of one order of magnitude drastically alters network dynamics, including the variability of the output range, the distribution of firing frequencies, and the duration of self-sustained activity. Moreover, comparing the model to a control condition with an equivalent number of (excitatory/inhibitory balanced) synapses, but removing all class-specific information (i.e. collapsing the network to homogeneous random connectivity) has surprisingly similar effects to downsizing the total number of neurons. The reduced-scale model is also compared directly with integrate-and-fire simulations, which capture considerably more physiological detail at the single-cell level, but still fail to reproduce the full behavioral complexity of the large-scale model. Thus network size, cell class diversity, and connectivity details may all be critical to generate self-sustained non-repetitive activity patterns.

L-Measure: a web-accessible tool for the analysis, comparison and search of digital reconstructions of neuronal morphologies.

L-Measure (LM) is a freely available software tool for the quantitative characterization of neuronal morphology. LM computes a large number of neuroanatomical parameters from 3D digital reconstruction files starting from and combining a set of core metrics. After more than six years of development and use in the neuroscience community, LM enables the execution of commonly adopted analyses as well as of more advanced functions. This report illustrates several LM protocols: (i) extraction of basic morphological parameters, (ii) computation of frequency distributions, (iii) measurements from user-specified subregions of the neuronal arbors, (iv) statistical comparison between two groups of cells and (v) filtered selections and searches from collections of neurons based on any Boolean combination of the available morphometric measures. These functionalities are easily accessed and deployed through a user-friendly graphical interface and typically execute within few minutes on a set of approximately 20 neurons. The tool is available at http://krasnow.gmu.edu/cn3 for either online use on any Java-enabled browser and platform or download for local execution under Windows and Linux.

Point Analysis in Java applied to histological images of the perforant pathway: a user's account.

The freeware Java tool Point Analysis in Java (PAJ), created to perform 3D point analysis, was tested in an independent laboratory setting. The input data consisted of images of the hippocampal perforant pathway from serial immunocytochemical localizations of the rat brain in multiple views at different resolutions. The low magnification set (x2 objective) comprised the entire perforant pathway, while the high magnification set (x100 objective) allowed the identification of individual fibers. A preliminary stereological study revealed a striking linear relationship between the fiber count at high magnification and the optical density at low magnification. PAJ enabled fast analysis for down-sampled data sets and a friendly interface with automated plot drawings. Noted strengths included the multi-platform support as well as the free availability of the source code, conducive to a broad user base and maximum flexibility for ad hoc requirements. PAJ has great potential to extend its usability by (a) improving its graphical user interface, (b) increasing its input size limit, (c) improving response time for large data sets, and (d) potentially being integrated with other Java graphical tools such as ImageJ.

Quantitative morphometry of hippocampal pyramidal cells: differences between anatomical classes and reconstructing laboratories.

The dendritic trees of hippocampal pyramidal cells play important roles in the establishment and regulation of network connectivity, synaptic plasticity, and firing dynamics. Several laboratories routinely reconstruct CA3 and CA1 dendrites to correlate their three-dimensional structure with biophysical, electrophysiological, and anatomical observables. To integrate and assess the consistency of the quantitative data available to the scientific community, we exhaustively analyzed 143 completely reconstructed neurons intracellularly filled and digitized in five different laboratories from 10 experimental conditions. Thirty morphometric parameters, including the most common neuroanatomical measurements, were extracted from all neurons. A consistent fraction of parameters (11 of 30) was significantly different between CA3 and CA1 cells. A considerably large number of parameters was also found that discriminated among neurons within the same morphological class, but reconstructed in different laboratories. These interlaboratory differences (8 of 30 parameters) far outweighed the differences between experimental conditions within a single lab, such as aging or preparation method (at most two significant parameters). The set of morphometrics separating anatomical regions and that separating reconstructing laboratories were almost entirely nonoverlapping. CA3 and CA1 neurons could be distinguished by global quantities such as branch order and Sholl distance. Differences among laboratories were largely due to local variables such as branch diameter and local bifurcation angles. Only one parameter (a ratio of branch diameters) separated both morphological classes and reconstructing laboratories. Compartmental simulations of electrophysiological activity showed that both differences between anatomical classes and reconstructing laboratories could dramatically affect the firing rate of these neurons under different experimental conditions.

Effects of dendritic morphology on CA3 pyramidal cell electrophysiology: a simulation study.

We investigated the effect of morphological differences on neuronal firing behavior within the hippocampal CA3 pyramidal cell family by using three-dimensional reconstructions of dendritic morphology in computational simulations of electrophysiology. In this paper, we report for the first time that differences in dendritic structure within the same morphological class can have a dramatic influence on the firing rate and firing mode (spiking versus bursting and type of bursting). Our method consisted of converting morphological measurements from three-dimensional neuroanatomical data of CA3 pyramidal cells into a computational simulator format. In the simulation, active channels were distributed evenly across the cells so that the electrophysiological differences observed in the neurons would only be due to morphological differences. We found that differences in the size of the dendritic tree of CA3 pyramidal cells had a significant qualitative and quantitative effect on the electrophysiological response. Cells with larger dendritic trees: (1) had a lower burst rate, but a higher spike rate within a burst, (2) had higher thresholds for transitions from quiescent to bursting and from bursting to regular spiking and (3) tended to burst with a plateau. Dendritic tree size alone did not account for all the differences in electrophysiological responses. Differences in apical branching, such as the distribution of branch points and terminations per branch order, appear to effect the duration of a burst. These results highlight the importance of considering the contribution of morphology in electrophysiological and simulation studies.