Specific patterns of neuronal firing induce changes in synaptic strength that may contribute to learning and memory. If the postsynaptic NMDA (N-methyl-D-aspartate) receptors are blocked, long-term potentiation (LTP) and long-term depression (LTD) of synaptic transmission and the learning of spatial information are prevented. The NMDA receptor can bind a protein known as postsynaptic density-95 (PSD-95), which may regulate the localization of and/or signalling by the receptor. In mutant mice lacking PSD-95, the frequency function of NMDA-dependent LTP and LTD is shifted to produce strikingly enhanced LTP at different frequencies of synaptic stimulation. In keeping with neural-network models that incorporate bidirectional learning rules, this frequency shift is accompanied by severely impaired spatial learning. Synaptic NMDA-receptor currents, subunit expression, localization and synaptic morphology are all unaffected in the mutant mice. PSD-95 thus appears to be important in coupling the NMDA receptor to pathways that control bidirectional synaptic plasticity and learning.

At excitatory synapses, the postsynaptic scaffolding protein postsynaptic density 95 (PSD-95) couples NMDA receptors (NMDARs) to the Ras GTPase-activating protein SynGAP. The close association of SynGAP and NMDARs suggests that SynGAP may have an important role in NMDAR-dependent activation of Ras signaling pathways, such as the MAP kinase pathway, and in synaptic plasticity. To explore this issue, we examined long-term potentiation (LTP), p42 MAPK (ERK2) signaling, and spatial learning in mice with a heterozygous null mutation of the SynGAP gene (SynGAP(-/+)). In SynGAP(-/+) mutant mice, the induction of LTP in the hippocampal CA1 region was strongly reduced in the absence of any detectable alteration in basal synaptic transmission and NMDAR-mediated synaptic currents. Although basal levels of activated ERK2 were elevated in hippocampal extracts from SynGAP(-/+) mice, NMDAR stimulation still induced a robust increase in ERK activation in slices from SynGAP(-/+) mice. Thus, although SynGAP may regulate the ERK pathway, its role in LTP most likely involves additional downstream targets. Consistent with this, the amount of potentiation induced by stimulation protocols that induce an ERK-independent form of LTP were also significantly reduced in slices from SynGAP(-/+) mice. An elevation of basal phospho-ERK2 levels and LTP deficits were also observed in SynGAP(-/+)/H-Ras(-)/- double mutants, suggesting that SynGAP may normally regulate Ras isoforms other than H-Ras. A comparison of SynGAP and PSD-95 mutants suggests that PSD-95 couples NMDARs to multiple downstream signaling pathways with very different roles in LTP and learning.

Recent studies demonstrated that the anatomical network of the human brain shows a "rich-club" organization. This complex topological feature implies that highly connected regions, hubs of the large-scale brain network, are more densely interconnected with each other than expected by chance. Rich-club nodes were traversed by a majority of short paths between peripheral regions, underlining their potential importance for efficient global exchange of information between functionally specialized areas of the brain. Network hubs have also been described at the microscale of brain connectivity (so-called "hub neurons"). Their role in shaping synchronous dynamics and forming microcircuit wiring during development, however, is not yet fully understood. The present study aimed to investigate the role of hubs during network development, using multi-electrode arrays and functional connectivity analysis during spontaneous multi-unit activity (MUA) of dissociated primary mouse hippocampal neurons. Over the first 4 weeks in vitro, functional connectivity significantly increased in strength, density, and size, with mature networks demonstrating a robust modular and small-world topology. As expected by a "rich-get-richer" growth rule of network evolution, MUA graphs were found to form rich-clubs at an early stage in development (14 DIV). Later on, rich-club nodes were a consistent topological feature of MUA graphs, demonstrating high nodal strength, efficiency, and centrality. Rich-club nodes were also found to be crucial for MUA dynamics. They often served as broker of spontaneous activity flow, confirming that hub nodes and rich-clubs may play an important role in coordinating functional dynamics at the microcircuit level.

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BackgroundNeural 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.ResultsWe used multielectrode arrays to record the development of spontaneous activity in cultured networks of either hippocampal or cortical neurons every 2 or 3 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 11 features. Three out of 11 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 and (3) hippocampal networks generate more robust theta-bursting patterns. Machine-learning techniques confirmed that these differences in patterning are sufficient to classify recordings reliably at any given age as either hippocampal or cortical networks.ConclusionsAlthough 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 the phenotype of different mutant mice. All code and data relating to this report are freely available for others to use.