The Structural E/I Balance Constrains the Early Development of Cortical Network Activity

Neocortical networks have a characteristic constant ratio in the number of glutamatergic projection neurons (PN) and GABAergic interneurons (IN), and deviations in this ratio are often associated with developmental neuropathologies. Cultured networks with defined cellular content allowed us to ask if initial PN/IN ratios change the developmental population dynamics, and how different ratios impact the physiological excitatory/inhibitory (E/I) balance and the network activity development. During the first week in vitro, the IN content modulated PN numbers, increasing their proliferation in networks with higher IN proportions. The proportion of INs in each network set remained similar to the initial plating ratio during the 4 weeks cultivation period. Results from additional networks generated with more diverse cellular composition, including early-born GABA neurons, suggest that a GABA-dependent mechanism may decrease the survival of additional INs. A large variation of the PN/IN ratio did not change the balance between isolated spontaneous glutamatergic and GABAergic postsynaptic currents charge transfer (E/I balance) measured in PNs or INs. In contrast, the E/I balance of multisynaptic bursts reflected differences in IN content. Additionally, the spontaneous activity recorded by calcium imaging showed that higher IN ratios were associated with increased frequency of network bursts combined with a decrease of participating neurons per event. In the 4th week in vitro, bursting activity was stereotypically synchronized in networks with very few INs but was more desynchronized in networks with higher IN proportions. These results suggest that the E/I balance of isolated postsynaptic currents in single cells may be regulated independently of PN/IN proportions, but the network bursts E/I balance and the maturation of spontaneous network activity critically depends upon the structural PN/IN ratio.

Bidirectional Cycling Dynamics of Living Neuronal Networks in Vitro

Phenomena of synchronization, rhythmogenesis and coherence found in brain networks are believed to be a dynamical substrate for cognitive functions such as learning and memory. However, it is still debated whether the rhythmic activity emerges from network morphology developed in neurogenesis or as a result of neuronal dynamics realized under certain conditions. In this research we found, that in neural networks formed in mature hippocampal cultures with high cellular density the spiking activity self-organized and converged to long, complex and rhythmically repeated superbursts. The superburst lasted tens of seconds and consisted of hundreds of short (50-100 ms) small bursts with a high spiking rate of 139.0 ± 78.6 Hz that can be associated with high-frequency oscillations in the hippocampus. In turn, the interval between peak burst activities in the range of 100-150 ms can be treated as a theta rhythm (11.2 ± 1.5 Hz). Distribution of spikes within the bursts was non-random, representing a set of well-defined space-time base patterns or motifs. We found that the long superburst can be classified into two types. Each type was associated with a unique direction of spike propagation and, hence, can be encoded by a binary sequence with random switching between the two “functional” states. Such precisely structured bidirectional rhythmic activity developed in self-organizing cultured networks were quite similar to what observed in the in vivo experiments.

Quantitative differences in developmental profiles of spontaneous activity in cortical and hippocampal cultures

Background: Neural circuits can spontaneously generate complex spatiotemporal firing patterns during development. This spontaneous activity is thought to help guide development of the nervous system. In this study, we had two aims. First, to characterise the changes in spontaneous activity in cultures of developing networks of either hippocampal or cortical neurons dissociated from mouse. Second, to assess whether there are any functional differences in the patterns of activity in hippocampal and cortical networks. Results: We used multielectrode arrays to record the development of spontaneous activity in cultured networks of either hippocampal or cortical neurons every two or three days for the first month after plating. Within a few days of culturing, networks exhibited spontaneous activity. This activity strengthened and then stabilised typically around 21 days in vitro. We quantified the activity patterns in hippocampal and cortical networks using eleven features. Three out of eleven features showed striking differences in activity between hippocampal and cortical networks. 1: Interburst intervals are less variable in spike trains from hippocampal cultures. 2: Hippocampal networks have higher correlations. 3: Hippocampal networks generate more robust theta bursting patterns. Machine learning techniques confirmed that these differences in patterning are sufficient to reliably classify recordings at any given age as either hippocampal or cortical networks. Conclusions: Although cultured networks of hippocampal and cortical networks both generate spontaneous activity that changes over time, at any given time we can reliably detect differences in the activity patterns. We anticipate that this quantitative framework could have applications in many areas, including neurotoxicity testing and for characterising phenotype of different mutant mice. All code and data relating to this report are freely available for others to use.