Circuit topology for synchronizing neurons--论文代写范文

同步峰值产生持久的突触可塑性,根据相对的突触前和突触后神经元，峰值不同步常常产生高阶复杂动力学。神经相关性研究解决拓扑结构，连接多个神经元。下面的论文代写范文进行详述。

Abstract
  Spike synchronization underlies information processing and storage in the brain. But how can neurons synchronize in a noisy network? By exploiting a high-speed (500–2,000 fps) multineuron imaging technique and a large-scale synapse mapping method, we directly compared spontaneous activity patterns and anatomical connectivity in hippocampal CA3 networks ex vivo. As compared to unconnected pairs, synaptically coupled neurons shared more common presynaptic neurons, received more correlated excitatory synaptic inputs, and emitted synchronized spikes with approximately 107 times higher probability. Importantly, common presynaptic parents per se synchronized more than unshared upstream neurons. Consistent with this, dynamic-clamp stimulation revealed that common inputs alone could not account for the realistic degree of synchronization unless presynaptic spikes synchronized among common parents. On a macroscopic scale, network activity was coordinated by a power-law scaling of synchronization, which engaged varying sets of densely interwired (thus highly synchronized) neuron groups. Thus, locally coherent activity converges on specific cell assemblies, thereby yielding complex ensemble dynamics. These segmentally synchronized pulse packets may serve as information modules that flow in associatively parallel network channels.

  Synchronized spikes prevail in cortical networks (1, 2). Their modulations are commonly found in relation to attention, sensory processing, and motor behaviors (3–8) and are implied in perceptual binding (9). From computational aspects, spike synchronization is crucial in information propagation (10, 11). As single synapses are weak and stochastic, spikes cannot propagate to a downstream network unless they synchronize. Moreover, synchronized spikes are known to induce long-lasting synaptic plasticity, depending on their relative timings between presynaptic and postsynaptic neurons (12, 13). Spikes do not synchronize only between a pair of neurons but also among a set of neurons, often yielding high-order complex dynamics, as in cell assemblies (14–17), synfire chains (10, 18), and neuronal avalanches (19). 

  The complex dynamics usually emerge through autoassociative recurrent networks in which neurons are sparsely interconnected to constitute relatively small groups. Thus, a neural correlation can report a local network state (20–22). Independent studies have addressed the topology underlying either “functional” (synchronous) or “anatomical” (synaptic) connectivity among multiple neurons (23–34), but very little is known about their relationship. In this work, we used high-speed functional multineuron calcium imaging (fMCI), large-scale synapse mapping, and multiple whole-cell and dynamic patchclamp recording techniques and directly compared spatiotemporal spike patterns with synaptic wiring architectures. We report that CA3 networks ex vivo are nonrandomly woven to facilitate local spike synchronization under globally coherent inhibitory backgrounds.

 Origin of Synchronization
  More synchronized neuron pairs were more likely to be synaptically linked. We do not think, however, that this synaptic link is enough to synchronize these neurons, because a single synapse is too weak to depolarize beyond the spike threshold. Rather, correlated synaptic inputs from multiple common presynaptic neurons (30–33, 45) are more plausibly causal of spike synchronization. Two lines of evidence are in favor of this hypothesis. First, ROTing revealed that synaptically coupled CA3 PC pairs shared numerically more presynaptic CA3 PCs. Second, double whole-cell recordings of neuron pairs revealed that more synchronized pairs received more correlated sEPSCs. We also found that common parent PCs were strongly synchronized. This indicates that these common parents are also under the further-upstream innervation by common “grandparent” PCs. This suggests synchronous activity flow, that is, synchronous pulse packets flow across densely connected neuron groups in recurrent networks. 

  This idea is supported by our dynamic clamp data showing that common presynaptic neurons need to be synchronized to evoke a realistic level of postsynaptic synchronization, although common inputs from randomly spiking neurons can do neurons to some extent. In the dynamic clamp experiments, however, we did not consider the dendritic properties. Dendrites exhibit nonlinear excitation through spatiotemporal input summation and dendritic spikes. It is also possible that synchronized spikes result from nonlinear dendritic computation with convergent inputs of synchronous activity into specific dendritic branches. Research into this possibility is under way in our laboratory with multiple patch-clamp recordings targeting dendrites (46).

 Cell Assemblies in Small-World Networks
  Consistent with previous reports showing that the functional and anatomical connectivity among individual neurons exhibits small-world architectures (26, 27, 47, 48), the CA3 networks also included small-world topology. The small-world network is theoretically believed to allow fast information transfer with low wiring costs (49), the coexistence of information segregation and integration (50), and synchronization (51). Neurons within a small-world cluster, classified by affinity propagation, were sparsely distributed in space. In hippocampal place cell activity recorded by multiple unit electrodes in vivo, it is also reported that synchronous cliques are dispersed across the electrodes (17). Despite this apparent randomness of neuron locations, within-group neurons were preferentially interconnected. This may emerge from target-selection mechanisms, such as activity-dependent synaptic plasticity. Moreover, synchronous CA3 neuron groups converged onto the same CA1 neurons. 

  Thus, the CA3-to-CA1 connectivity forms relatively independent routes that carry CA3 ensemble activities to specific CA1 neuron subsets (Fig. S8). Synchronous modules may serve as endogenous building blocks that embody the diversity and complexity of information processing in associative and parallel networks. Coherent Inhibitory Networks. In the rat neocortex, the axons of inhibitory neurons highly arborize, twisting and turning, seemingly rummaging among their postsynaptic targets (52). Therefore, single interneurons may promiscuously provide nearby PCs with correlated inhibitory inputs. Moreover, interneurons are reciprocally connected through synaptic contacts and gap junction (53–55). Thus, their interplay may give rise to globally coherent inhibition of PC networks (56). Indeed we found that sIPSCs were correlated between virtually all PC pairs. Inhibitory inputs limit the window available for temporal summation and increase the temporal precision of PC firing (57). They also entrain network activity by interacting with intrinsic oscillatory mechanisms of PCs (58). We thus speculate that interneurons couple relatively independent PC subgroups and orchestrate complex network synchronization.(论文代写)

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