A neuron membrane mesh representation for visualization of electrophysiological simulations

We present a process to automatically generate three-dimensional mesh representations of the complex, arborized cell membrane surface of cortical neurons (the principal information processing cells of the brain) from nonuniform morphological measurements. Starting from manually sampled morphological points (3D points and diameters) from neurons in a brain slice preparation, we construct a polygonal mesh representation that realistically represents the continuous membrane surface, closely matching the original experimental data. A mapping between the original morphological points and the newly generated mesh enables simulations of electrophysiolgical activity to be visualized on this new membrane representation. We compare the new mesh representation with the state of the art and present a series of use cases and applications of this technique to visualize simulations of single neurons and networks of multiple neurons.

Developmental and spatial expression pattern of syntaxin 13 in the mouse central nervous system

Harald Hirling, Juan-Carlos Sarria

Vesicular transport involves SNARE (soluble- N-ethylmaleimide-sensitive-factor-attachment-protein-receptor) proteins on transport vesicles and on target membranes. Syntaxin 13 is a SNARE enriched in brain, associated with recycling endosomes; its overexpression in PC12 cells promotes neurite outgrowth. This suggests an important role for receptor recycling during neuronal differentiation. Here we describe the spatiotemporal pattern of syntaxin 13 expression during mouse brain development. During early embryogenesis (E12-E15), it was found in the forebrain ventricular zone and in primary motor and sensory neurons in the brainstem, spinal cord and sensory ganglia. In the forebrain at E15, syntaxin 13 was not detected in neuroblasts in the intermediate zone of the embryonic hemispheric wall, while there was labeling in cortical neurons in deeper layers starting at E15-18, and progressively in later-generated neurons up to layer II around P6. Syntaxin 13 reached maximal expression in all brain divisions at about P7, followed by a decrease, with heterogeneous neuron populations displaying various staining intensities in adult brain. While usually restricted to the soma of neurons, we transiently detected syntaxin 13 in dendrites of pyramidal neurons during the first postnatal week. In conclusion, the developmentally regulated syntaxin 13 expression in various neuronal populations is consistent with its involvement in endocytic trafficking and neurite outgrowth.

2002

Extraction of network topology from multi-electrode recordings: is there a small-world effect?

Joao Emanuel Felipe Gerhard, Wulfram Gerstner

The simultaneous recording of the activity of many neurons poses challenges for multivariate data analysis. Here, we propose a general scheme of reconstruction of the functional network from spike train recordings. Effective, causal interactions are estimated by fitting generalized linear models on the neural responses, incorporating effects of the neurons' self-history, of input from other neurons in the recorded network and of modulation by an external stimulus. The coupling terms arising from synaptic input can be transformed by thresholding into a binary connectivity matrix which is directed. Each link between two neurons represents a causal influence from one neuron to the other, given the observation of all other neurons from the population. The resulting graph is analyzed with respect to small-world and scale-free properties using quantitative measures for directed networks. Such graph-theoretic analyses have been performed on many complex dynamic networks, including the connectivity structure between different brain areas. Only few studies have attempted to look at the structure of cortical neural networks on the level of individual neurons. Here, using multi-electrode recordings from the visual system of the awake monkey, we find that cortical networks lack scale-free behavior, but show a small, but significant small-world structure. Assuming a simple distance-dependent probabilistic wiring between neurons, we find that this connectivity structure can account for all of the networks' observed small-world-ness. Moreover, for multi-electrode recordings the sampling of neurons is not uniform across the population. We show that the small-world-ness obtained by such a localized sub-sampling overestimates the strength of the true small-world structure of the network. This bias is likely to be present in all previous experiments based on multi-electrode recordings.

Frontiers Research Foundation2011

Extraction of network topology from multi-electrode recordings: is there a small-world effect?

Joao Emanuel Felipe Gerhard, Wulfram Gerstner

Frontiers Research Foundation2011