Energy-efficient encoding by shifting spikes in neocortical neurons.

The speed of computations in neocortical networks critically depends on the ability of populations of spiking neurons to rapidly detect subtle changes in the input and translate them into firing rate changes. However, high sensitivity to perturbations may lead to explosion of noise and increased energy consumption. Can neuronal networks reconcile the requirements for high sensitivity, operation in a low-noise regime, and constrained energy consumption? Using intracellular recordings in slices from the rat visual cortex, we show that layer 2/3 pyramidal neurons are highly sensitive to minor input perturbations. They can change their population firing rate in response to small artificial excitatory postsynaptic currents (aEPSCs) immersed in fluctuating noise very quickly, within 2-2.5 ms. These quick responses were mediated by the generation of new, additional action potentials (APs), but also by shifting spikes into the response peak. In that latter case, the spike count increase during the peak and the decrease after the peak cancelled each other, thus producing quick responses without increases in total spike count and associated energy costs. The contribution of spikes from one or the other source depended on the aEPSCs timing relative to the waves of depolarization produced by ongoing activity. Neurons responded by shifting spikes to aEPSCs arriving at the beginning of a depolarization wave, but generated additional spikes in response to aEPSCs arriving towards the end of a wave. We conclude that neuronal networks can combine high sensitivity to perturbations and operation in a low-noise regime. Moreover, certain patterns of ongoing activity favor this combination and energy-efficient computations.

Measurements of neuronal morphological variation across the rat neocortex.

Neuron morphology is highly variable across the mammalian brain. It is thought that these attributes of neuronal cell shape, such as soma surface area and branching frequency, are determined by biological function and information processing. In this study, a large data set of neurons across the rat neocortex were clustered by their anatomical characters for evidence of distinctiveness among neocortical regions and the somatosensory layers. This data set of neuronal morphologies was compiled from 31 different lab sources with a validation procedure so that data records are potentially comparable across research studies. With this large set of heterogeneous data and by clustering analysis, this study shows that neuronal morphological traits overlap among neocortical and somatosensory regions. In the context of past neuroanatomical studies, this result is not congruent with tissue level analysis and strongly suggests further sampling of neuronal data to lessen the effect of confounding factors, such as the influence of different methodologies from use of heterogeneous samples of neuronal data.

Development of Cortical Pyramidal Cell and Interneuronal Dendrites: a Role for Kainate Receptor Subunits and NETO1.

During neuronal development, AMPA receptors (AMPARs) and NMDA receptors (NMDARs) are important for neuronal differentiation. Kainate receptors (KARs) are closely related to AMPARs and involved in the regulation of cortical network activity. However, their role for neurite growth and differentiation of cortical neurons is unclear. Here, we used KAR agonists and overexpression of selected KAR subunits and their auxiliary neuropilin and tolloid-like proteins, NETOs, to investigate their influence on dendritic growth and network activity in organotypic cultures of rat visual cortex. Kainate at 500 nM enhanced network activity and promoted development of dendrites in layer II/III pyramidal cells, but not interneurons. GluK2 overexpression promoted dendritic growth in pyramidal cells and interneurons. GluK2 transfectants were highly active and acted as drivers for network activity. GluK1 and NETO1 specifically promoted dendritic growth of interneurons. Our study provides new insights for the roles of KARs and NETOs in the morphological and physiological development of the visual cortex.

Fractal dimension of apical dendritic arborization differs in the superficial and the deep pyramidal neurons of the rat cerebral neocortex.

Pyramidal neurons of the mammalian cerebral cortex have specific structure and pattern of organization that involves the presence of apical dendrite. Morphology of the apical dendrite is well-known, but quantification of its complexity still remains open. Fractal analysis has proved to be a valuable method for analyzing the complexity of dendrite morphology. The aim of this study was to establish the fractal dimension of apical dendrite arborization of pyramidal neurons in distinct neocortical laminae by using the modified box-counting method. A total of thirty, Golgi impregnated neurons from the rat brain were analyzed: 15 superficial (cell bodies located within lamina II-III), and 15 deep pyramidal neurons (cell bodies situated within lamina V-VI). Analysis of topological parameters of apical dendrite arborization showed no statistical differences except in total dendritic length (p=0.02), indicating considerable homogeneity between the two groups of neurons. On the other hand, average fractal dimension of apical dendrite was 1.33±0.06 for the superficial and 1.24±0.04 for the deep cortical neurons, showing statistically significant difference between these two groups (p<0.001). In conclusion, according to the fractal dimension values, apical dendrites of the superficial pyramidal neurons tend to show higher structural complexity compared to the deep ones.

Phosphoinositide-3-kinases p110α and p110ß mediate S phase entry in astroglial cells in the marginal zone of rat neocortex.

In cells cultured from neocortex of newborn rats, phosphoinositide-3-kinases of class I regulate the DNA synthesis in a subgroup of astroglial cells. We have studied the location of these cells as well as the kinase isoforms which facilitate the S phase entry. Using dominant negative (dn) isoforms as well as selective pharmacological inhibitors we quantified S phase entry by nuclear labeling with bromodeoxyuridine (BrdU). Only in astroglial cells harvested from the marginal zone (MZ) of the neocortex inhibition of phosphoinositide-3-kinases reduced the nuclear labeling with BrdU, indicating that neocortical astroglial cells differ in the regulation of proliferation. The two kinase isoforms p110α and p110ß were essential for S phase entry. p110α diminished the level of the p27(Kip1) which inactivates the complex of cyclin E and CDK2 necessary for entry into the S phase. p110ß phosphorylated and inhibited glycogen synthase kinase-3ß which can prevent S-phase entry. Taken together, both isoforms mediated S phase in a subgroup of neocortical astroglial cells and acted via distinct pathways.