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.

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.

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.

Conditional firing probabilities in cultured neuronal networks: a stable underlying structure in widely varying spontaneous activity patterns.

To properly observe induced connectivity changes after training sessions, one needs a network model that describes individual relationships in sufficient detail to enable observation of induced changes and yet reveals some kind of stability in these relationships. We analyzed spontaneous firing activity in dissociated rat cortical networks cultured on multi-electrode arrays by means of the conditional firing probability. For all pairs (i, j) of the 60 electrodes, we calculated conditional firing probability (CFP(i,j)[tau]) as the probability of an action potential at electrode j at t = tau, given that one was detected at electrode i at t = 0. If a CFP(i,j)[tau] distribution clearly deviated from a flat one, electrodes i and j were considered to be related. For all related electrode pairs, a function was fitted to the CFP-curve to obtain parameters for 'strength' and 'delay' (i.e. maximum and latency of the maximum of the curve) of each relationship. In young cultures the set of identified relationships changed rather quickly. At 16 days in vitro (DIV) 50% of the set changed within 2 days. Beyond 25 DIV this set stabilized: during 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, with coefficients of variation (100 x SD/mean) around 25% in periods of approximately 10 h. CFP analysis provides a robust method to describe the underlying probabilistic structure of highly varying spontaneous activity in cultured cortical networks. It may offer a suitable basis for plasticity studies, in the case of changes in the probabilistic structure. CFP analysis monitors all pairs of electrodes instead of just a selected one. Still, it is likely to describe the network in sufficient detail to detect subtle changes in individual relationships.

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.

Threshold for efferent bladder nerve firing in the rat.

In this study, the mechanism involved in the initiation of voiding was investigated. Bladder pressure and bladder and urethral nerve activity were recorded in the anesthetized rat. Bladder nerve activity was resolved into afferent and efferent activity by means of a theoretical model. The beginning of an active bladder contraction was defined as the onset of bladder efferent firing at a certain time (t0). From t0 onward, bladder efferent activity increased linearly during deltat seconds (rise time) to a maximum. The pressure at t0 was 1.0 +/- 0.4 kPa, the afferent nerve activity at t0 was 2.0 +/- 0.6 microV (53 +/- 15% of maximum total nerve activity), and deltat was 11 +/- 13 s. Between contractions the afferent activity at t0 was never exceeded. Urethral afferent nerve activity started at bladder pressures of 2.1 +/- 1.1 kPa. Therefore, we concluded that urethral afferent nerve activity does not play a role in the initiation of bladder contractions; voiding contractions presumably are initiated by bladder afferent nerve activity exceeding a certain threshold.

Neurophysiological modeling of voiding in rats: bladder pressure and postganglionic bladder nerve activity.

A model was developed that describes the relations between bladder pressure and both efferent and afferent nerve activity in postganglionic bladder nerves in urethan-anesthetized rats. Nerve activity was calculated as the 100-ms time integral of the rectified nerve signal. Afferent and efferent nerve signals were measured separately by crushing the nerve proximally or distally. A linear relation was found between bladder pressure and afferent nerve activity (fit error < 7%), and the relation between bladder pressure and efferent nerve activity was described by a low-pass filter (fit error < 90%). In most experiments, combined (efferent and afferent) nerve activity was measured. Absence of efferent nerve activity was assumed during the pressure decrease immediately after voiding. From this episode, the afferent nerve activity was estimated for the entire measurement. Efferent nerve activity was then estimated assuming linear addition in the bidirectionally conducting nerves. The model described the measured data very well (fit error < 7%), and the model parameters showed a good reproducibility in each rat (SD was approximately 30% of the mean).