Network structure determines patterns of network reorganization during adult neurogenesis

New cells are generated throughout life and integrate into the hippocampus via the process of adult neurogenesis. Epileptogenic brain injury induces many structural changes in the hippocampus, including the death of interneurons and altered connectivity patterns. The pathological neurogenic niche is associated with aberrant neurogenesis, though the role of the network-level changes in development of epilepsy is not well understood. In this paper, we use computational simulations to investigate the effect of network environment on structural and functional outcomes of neurogenesis. We find that small-world networks with external stimulus are able to be augmented by activity-seeking neurons in a manner that enhances activity at the stimulated sites without altering the network as a whole. However, when inhibition is decreased or connectivity patterns are changed, new cells are both less responsive to stimulus and the new cells are more likely to drive the network into bursting dynamics. Our results suggest that network-level changes caused by epileptogenic injury can create an environment where neurogenic reorganization can induce or intensify epileptic dynamics and abnormal integration of new cells.Comment: 28 pages, 10 figure

Internetwork and intranetwork communications during bursting dynamics: Applications to seizure prediction

We use a simple dynamical model of two interacting networks of integrate-and-fire neurons to explain a seemingly paradoxical result observed in epileptic patients indicating that the level of phase synchrony declines below normal levels during the state preceding seizures (preictal state). We model the transition from the seizure free interval (interictal state) to the seizure (ictal state) as a slow increase in the mean depolarization of neurons in a network corresponding to the epileptic focus. We show that the transition from the interictal to preictal and then to the ictal state may be divided into separate dynamical regimes: the formation of slow oscillatory activity due to resonance between the two interacting networks observed during the interictal period, structureless activity during the preictal period when the two networks have different properties, and bursting dynamics driven by the network corresponding to the epileptic focus. Based on this result, we hypothesize that the beginning of the preictal period marks the beginning of the transition of the epileptic network from normal activity toward seizing

Implications of the precision data for very light Higgs boson scenario in 2HDM, 2

We present an up-to-date analysis of the constraints imposed bythe precision data on the ($CP-$ conserving) Two-Higgs-Doublet Model of type II, with emphasis on the possible existence of very light neutral (pseudo)scalar Higgs boson with mass below 20--30 GeV. We show that even in the presence of such light particles, the 2HDM(II) can describe the electroweak data with precision comparable to that given by the SM. Particularly interesting lower limits on the mass of the lighter neutral $CP-$even scalar $h^0$ are obtained in the scenario with a light $CP-$odd Higgs boson $A^0$ and large $\tan\beta$

Structural network heterogeneities and network dynamics: a possible dynamical mechanism for hippocampal memory reactivation

The hippocampus has the capacity for reactivating recently acquired memories [1-3] and it is hypothesized that one of the functions of sleep reactivation is the facilitation of consolidation of novel memory traces [4-11]. The dynamic and network processes underlying such a reactivation remain, however, unknown. We show that such a reactivation characterized by local, self-sustained activity of a network region may be an inherent property of the recurrent excitatory-inhibitory network with a heterogeneous structure. The entry into the reactivation phase is mediated through a physiologically feasible regulation of global excitability and external input sources, while the reactivated component of the network is formed through induced network heterogeneities during learning. We show that structural changes needed for robust reactivation of a given network region are well within known physiological parameters [12,13].Comment: 16 pages, 5 figure

The interplay of intrinsic excitability and network topology in spatiotemporal pattern generation in neural networks

http://deepblue.lib.umich.edu/bitstream/2027.42/109555/1/12868_2014_Article_3550.pd

Ultrasound Investigations of Orbital Quadrupolar Ordering in UPd_3

For a high-quality single crystal of UPd_3 we present the relevant elastic constants and ultrasonic attenuation data. In addition to the magnetic phase transition at T_2=4.4 +/- 0.1K and the quadrupolar transition at T_1~6.8K, we find orbital ordering at T_0=7.6 +/- 0.1K concomitant with a symmetry change from hexagonal to orthorhombic. A striking feature is the splitting of the phase transition at T_1 into a second-order transition at T_{+1}=6.9 +/- 0.05K and a first-order transition at T_{-1}=6.7 +/- 0.05K. For the four phase transitions, the quadrupolar order parameters and the respective symmetry changes are specified.Comment: 14 pages (RevTex), 3 eps-figures, accepted by PR

A computational study on altered theta-gamma coupling during learning and phase coding

There is considerable interest in the role of coupling between theta and gamma oscillations in the brain in the context of learning and memory. Here we have used a neural network model which is capable of producing coupling of theta phase to gamma amplitude firstly to explore its ability to reproduce reported learning changes and secondly to memory-span and phase coding effects. The spiking neural network incorporates two kinetically different GABAA receptor-mediated currents to generate both theta and gamma rhythms and we have found that by selective alteration of both NMDA receptors and GABAA,slow receptors it can reproduce learning-related changes in the strength of coupling between theta and gamma either with or without coincident changes in theta amplitude. When the model was used to explore the relationship between theta and gamma oscillations, working memory capacity and phase coding it showed that the potential storage capacity of short term memories, in terms of nested gamma-subcycles, coincides with the maximal theta power. Increasing theta power is also related to the precision of theta phase which functions as a potential timing clock for neuronal firing in the cortex or hippocampus