Experimental analysis and computational modeling of interburst intervals in spontaneous activity of cortical neuronal culture

Rhythmic bursting is the most striking behavior of cultured cortical networks and may start in the second week after plating. In this study, we focus on the intervals between spontaneously occurring bursts, and compare experimentally recorded values with model simulations. In the models, we use standard neurons and synapses, with physiologically plausible parameters taken from literature. All networks had a random recurrent architecture with sparsely connected neurons. The number of neurons varied between 500 and 5,000. We find that network models with homogeneous synaptic strengths produce asynchronous spiking or stable regular bursts. The latter, however, are in a range not seen in recordings. By increasing the synaptic strength in a (randomly chosen) subset of neurons, our simulations show interburst intervals (IBIs) that agree better with in vitro experiments. In this regime, called weakly synchronized, the models produce irregular network bursts, which are initiated by neurons with relatively stronger synapses. In some noise-driven networks, a subthreshold, deterministic, input is applied to neurons with strong synapses, to mimic pacemaker network drive. We show that models with such “intrinsically active neurons” (pacemaker-driven models) tend to generate IBIs that are determined by the frequency of the fastest pacemaker and do not resemble experimental data. Alternatively, noise-driven models yield realistic IBIs. Generally, we found that large-scale noise-driven neuronal network models required synaptic strengths with a bimodal distribution to reproduce the experimentally observed IBI range. Our results imply that the results obtained from small network models cannot simply be extrapolated to models of more realistic size. Synaptic strengths in large-scale neuronal network simulations need readjustment to a bimodal distribution, whereas small networks do not require such change

Neurophysiological modeling of Voiding in Rats

Like man, most animals need a regular supply of nutriments. Eating and drinking cater for this need, but not with 100% efficiency. A considerable part of the conswned goods are expelled from the body as defecation. Waste products from the blood are filtered by the kidneys and excreted as urine. 1ms process continues throughout the day. In many situations, however, it would be very inconvenient to be expelling urine. Animals that leak urine continuously are more easily traced by preditors than the ones that don't. Besides this, for mankind it is socially intolerable at certain moments. Nature supplied q solution that enables storage of urine until a convenient moment for voiding: the bladder. Upon desire the bladder contracts and urine is expelled through the urethra, which, with the bladder, constitutes ti,e lower urinary tract. Thus the bladder owner controls when and where to expel urine

Intra-burst firing characteristics as network state parameters

Introduction \ud In our group we are aiming to demonstrate learning and memory capabilities of cultured networks of cortical neurons. A first step is to identify parameters that accurately describe changes in the network due to learning. Usually, such parameters are calculated from the responses to test-stimuli before and after a learning experiment. We propose that parameters should be calculated from the spontaneous activity before and after a learning experiment, as the applying of test-stimuli itself may alter the network. Since bursting is dominant in our cultures, we have investigated its spatio-temporal structure. \ud \ud Methods \ud Networks of cortical neurons were cultured on a MEA. Over a period from 9 to 35 DIV, the spontaneous activity has been measured on a regular basis. Measurements on a single day are always continuous; otherwise cultures are kept in a stove under controlled conditions (37 ˚C, 5% CO2, 100% humidity). Network bursts were detected by analysing the Array-Wide Spiking Rate (AWSR, the sum of activity over all electrodes). Next, we estimated the instantaneous AWSR during a burst by convolving spike-occurrences with a Gaussian function. We investigated the changes in burst profiles over time by aligning them to their peak AWSR. In 4 hour recording sessions, we grouped the burst profiles over 1 hour, resulting in 4 average burst profiles per day. In addition, a sufficient amount of aligned bursts yielded enough data to calculate the contribution of each recording site. \ud \ud Results \ud The burst profiles, calculated over a period of 1 hour, generally show little variation (figure 1). In subsequent hours, the profiles gradually change shape. Over a period of days however, the shape can change dramatically (figure 2). The relatively slow changes over the period of hours indicate an underlying probabilistic structure in the AWSR during bursts. The apparent structure in the burst profiles result from the relationships between individual recording sites, and thus also on the connectivity in the neural network. This is revealed in more detail by showing the contributions of individual sites (figure 3). The spike envelopes have a shape that is too detailed to be described accurately by a small set of parameters. \ud \ud Discussion \ud The burst profiles prove to be stable over a period of one hour, and gradually change their shape over several hours, as has also been suggested in [1]. The day-to-day changes in burst profiles may be the result of these gradual changes, thereby suggesting an intrinsically changing network. However, they can also be the result of putting the cultures back in the stove. The spike envelopes per recording site offer more detailed descriptions of the network state than the burst profiles. This may however be the amount of detail required to reveal the changes made during learning experiments. A subsequent refinement can be made by identifying distinct subgroups of bursts, as has been suggested in [2]

Ghrelin accelerates synapse formation and activity development in cultured cortical networks

Background: While ghrelin was initially related to appetite stimulation and growth hormone secretion, it also has a neuroprotective effect in neurodegenerative diseases and regulates cognitive function. The cellular basis of those processes is related to synaptic efficacy and plasticity. Previous studies have shown that ghrelin not only stimulates synapse formation in cultured cortical neurons and hippocampal slices, but also alters some of the electrophysiological properties of neurons in the hypothalamus, amygdala and other subcortical areas. However, direct evidence for ghrelin's ability to modulate the activity in cortical neurons is not available yet. In this study, we investigated the effect of acylated ghrelin on the development of the activity level and activity patterns in cortical neurons, in relation to its effect on synaptogenesis. Additionally, we quantitatively evaluated the expression of the receptor for acylated ghrelin - growth hormone secretagogue receptor-1a (GHSR-1a) during development. Results: We performed electrophysiology and immunohistochemistry on dissociated cortical cultures from neonates, treated chronically with acylated ghrelin. On average 76 � 4.6% of the cortical neurons expressed GHSR-1a. Synapse density was found to be much higher in ghrelin treated cultures than in controls across all age groups (1, 2 or 3 weeks). In all cultures (control and ghrelin treated), network activity gradually increased until it reached a maximum after approximately 3 weeks, followed by a slight decrease towards a plateau. During early developmental stages (1-2 weeks), the activity was much higher in ghrelin treated cultures and consequently, they reached the plateau value almost a week earlier than controls. Conclusions: Acylated ghrelin leads to earlier network formation and activation in cultured cortical neuronal networks, the latter being a possibly consequence of accelerated synaptogenesis

Pudendal nerve stimulation induces urethral contraction and relaxation

In this study we measured urethral pressure changes in response to efferent pudendal nerve stimulation in rats. All other neural pathways to the urethra were transected, and the urethra was continuously perfused. We found fast twitch-like contractions, superimposed on a slow relaxation. The amplitude of the twitches was independent of the stimulation frequency below 26 Hz, whereas the relaxation depended highly on this frequency. The twitches were caused by striated urethral muscles, and the relaxation was caused by smooth muscles. Both were mediated by acetylcholine. We calculated the effective urethral relaxation as the absolute relaxation multiplied by the time fraction between the twitches. Maximum effective relaxation occurred at 8-10 Hz, exactly the frequency of spontaneous oscillations during bladder voiding in rats. Although the oscillatory sphincter contractions in rats during voiding may be needed in other mechanisms for efficient voiding, our data suggest that they may be a side effect of the actual purpose: urethral relaxation

Acyl Ghrelin Improves Synapse Recovery in an In Vitro Model of Postanoxic Encephalopathy

Comatose patients after cardiac arrest have a poor prognosis. Approximately half never awakes as a result of severe diffuse postanoxic encephalopathy. Several neuroprotective agents have been tested, however without significant effect. In the present study, we used cultured neuronal networks as a model system to study the general synaptic damage caused by temporary severe hypoxia and the possibility to restrict it by ghrelin treatment. Briefly, we applied hypoxia (pO2 lowered from 150 to 20 mmHg) during 6 h in 55 cultures. Three hours after restoration of normoxia, half of the cultures were treated with ghrelin for 24 h, while the other, non-supplemented, were used as a control. All cultures were processed immunocytochemically for detection of the synaptic marker synaptophysin. We observed that hypoxia led to drastic decline of the number of synapses, followed by some recovery after return to normoxia, but still below the prehypoxic level. Additionally, synaptic vulnerability was selective: large- and small-sized neurons were more susceptible to synaptic damage than the medium-sized ones. Ghrelin treatment significantly increased the synapse density, as compared with the non-treated controls or with the prehypoxic period. The effect was detected in all neuronal subtypes. In conclusion, exogenous ghrelin has a robust impact on the recovery of cortical synapses after hypoxia. It raises the possibility that ghrelin or its analogs may have a therapeutic potential for treatment of postanoxic encephalopathy

Plasmon scattering from single sub-wavelength holes

We map the complex electric fields associated with the scattering of surface plasmon polaritons by single sub-wavelength holes of different sizes in thick gold films. We identify and quantify the different modes associated with this event, including a radial surface wave with an angularly isotropic amplitude. This wave is shown to arise from the out-of-plane electric dipole induced in the hole, and we quantify the corresponding polarizability, which is in excellent agreement with electromagnetic theory. Time-resolved measurements reveal a time-delay of 38? +/- 18 fs between the surface plasmon polariton and the radial wave, which we attribute to the interaction with a broad hole resonance

Cultured cortical networks described by conditional firing probabilities

Networks of cortical neurons were grown over multi electrode arrays to enable simultaneous measu-rement of action potentials from 60 electrodes. All possible pairs of electrodes (i,j) were tested for syn-chronized activity. We calculated conditional firing probability (CFPi,j[τ]) as the probability of an action potential at electrode j at t=τ, given that a spike was detected at i at t=0. If a CFPi,j[τ] distribution clearly deviated from flat, electrodes i and j were considered related. A function was fitted to each CFP-curve to obtain parameters for strength and delay. In young cultures the set of identified relationships changed rather quickly. At 16 days in vitro (DIV) 50% of the set changed within one day. Beyond 25 DIV this set stabilized: during a period of a week more than 50% of the set remained intact. Most individual relationships developed rather gradually. Moreover, beyond 25 DIV relational strength appeared quite stable during periods of ≈ 10 hours, with coefficients of variation (100×SD/mean) of ≈ 25% on average. CFP analysis provides a robust method to describe the stable underlying probabilistic structure of highly varying spontaneous activity in cultured cortical networks. It may offer a suitable basis for plasticity studies, in which induced changes should exceed spontaneous fluctuations. CFP analysis is likely to describe the network in sufficient detail to detect subtle changes in individual relationships. Analysis of data continuously recorded for ≈ 6 weeks, showed that highest stability is reached after ≈ 25 DIV, suggesting the 4th and 5th week as a suitable period for plasticity studies.\ud \u