J. le Feber

Network bursts in cortical cultures are best simulated using pacemaker neurons and adaptive synapses

One of the most specific and exhibited features in the electrical activity of dissociated cultured neural networks (NNs) is the phenomenon of synchronized bursts, whose profiles vary widely in shape, width and firing rate. On the way to understanding the organization and behavior of biological NNs, we reproduced those features with random connectivity network models with 5,000 neurons. While the common approach to induce bursting behavior in neuronal network models is noise injection, there is experimental evidence suggesting the existence of pacemaker-like neurons. In our simulations noise did evoke bursts, but with an unrealistically gentle rising slope. We show that a small subset of ‘pacemaker’ neurons can trigger bursts with a more realistic profile. We found that adding pacemaker-like neurons as well as adaptive synapses yield burst features (shape, width, and height of the main phase) in the same ranges as obtained experimentally. Finally, we demonstrate how changes in network connectivity, transmission delays, and excitatory fraction influence network burst features quantitatively.

Latency-related development of functional connections in cultured cortical networks

To study plasticity, we cultured cortical networks on multielectrode arrays, enabling simultaneous recording from multiple neurons. We used conditional firing probabilities to describe functional network connections by their strength and latency. These are abstract representations of neuronal pathways and may arise from direct pathways between two neurons or from a common input. Functional connections based on direct pathways should reflect synaptic properties. Therefore, we searched for long-term potentiation (this mechanism occurs in vivo when presynaptic action potentials precede postsynaptic ones with interspike intervals up to approximately 20 ms) in vitro. To investigate if the strength of functional connections showed a similar latency-related development, we selected periods of monotonously increasing or decreasing strength. We observed increased incidence of short latencies (5-30 ms) during strengthening, whereas these rarely occurred during weakening. Furthermore, we saw an increased incidence of 40-65 ms latencies during weakening. Conversely, functional connections tended to strengthen in periods with short latency, whereas strengthening was significantly less than average during long latency. Our data suggest that functional connections contain information about synaptic connections, that conditional firing probability analysis is sensitive enough to detect it and that a substantial fraction of all functional connections is based on direct pathways.

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 changes.

Using cognitive modeling for requirements engineering in anesthesiology

Cognitive modeling is a complexity reducing method to describe significant cognitive processes under a specified research focus. Here, a cognitive process model for decision making in anesthesiology is presented and applied in requirements engineering. Three decision making situations of anesthetists are distinguished, which depend on the state of the patient. For every decision making situation, different requirements of information supply to support decision making of anesthetists can be defined without additional input of the anesthetist. We developed a prototype of a decision support system for familiar situations and define the specifications of a system to support urgent situations. More research about presenting relevant information is needed to support the third decision making situation, diagnosing.

Exogenous α-synuclein hinders synaptic communication in cultured cortical primary rat neurons

Amyloid aggregates of the protein α-synuclein (αS) called Lewy Bodies (LB) and Lewy Neurites (LN) are the pathological hallmark of Parkinson’s disease (PD) and other synucleinopathies. We have previously shown that high extracellular αS concentrations can be toxic to cells and that neurons take up αS. Here we aimed to get more insight into the toxicity mechanism associated with high extracellular αS concentrations (50–100 μM). High extracellular αS concentrations resulted in a reduction of the firing rate of the neuronal network by disrupting synaptic transmission, while the neuronal ability to fire action potentials was still intact. Furthermore, many cells developed αS deposits larger than 500 nm within five days, but otherwise appeared healthy. Synaptic dysfunction clearly occurred before the establishment of large intracellular deposits and neuronal death, suggesting that an excessive extracellular αS concentration caused synaptic failure and which later possibly contributed to neuronal death.

Regulatory effects of orexin A on neuronal networks formation and activity in vitro

Orexin A (OXA) is a neuropeptide, isolated from neurons in the hypothalamus, which regulates various brain activities, including wakefulness and higher brain functions like learning and memory. There is a growing interest in OXA’s role in neurodegenerative diseases with respect to non-motor symptoms such as sleep-, attention- and cognitive- disorders. Recent studies in Parkinson’s and Alzheimer’s patients found lower concentrations of OXA in the prefrontal cortex and cerebro-spinal fluid. It is widely assumed that deteriorated cognitive processes are related to impaired network connectivity. However, little is known about the effects of OXA on the network activity and synaptogenesis. Therefore, we investigated the development of activity in dissociated cortical neurons of rat chronically treated with 0.5 µM OXA for three weeks. Network activity was recorded with multi electrode arrays. Additionally, after one-, two- or three weeks cultures were stained immunocytochemically for detection of the presynaptic marker synaptophysin. OXA treated cultures become spontaneously active earlier, and the plateau of their activity was higher than in controls. Immunostaining revealed that the synaptic density was much higher in OXA treated cultures in all age groups. Hence, OXA has a strong stimulating effect on network formation and activity, the latter probably being a consequence of the accelerated synaptogenesis. These results indicate that drugs, based on OXA are potential candidates for prevention and treatment of disorders associated with neuronal connectivity and activity decline.

Network bursts in cortical neuronal cultures ‘Noise- versus pacemaker’- driven neural network simulations

Dissociated neuronal cultures provide a useful platform to study behavior and development of biological neural networks. Isolated from external inputs neural cultures generate electrical activity of their own, showing several features. The most striking feature is the phenomenon of, more or less regular, network bursts, i.e. simultaneous firing of many neurons in a relatively short time window. In this paper we address the issue of spontaneous bursting activity in cortical neuronal cultures and explain what might cause this collective behavior using computer simulations of two different neural network models. While the common approach to activate a passive network is done by introducing synaptic noise, we show that a small subset of pacemaker neurons can trigger network bursts which better resemble experimental bursts.