Synaptic mechanisms of pattern completion in the hippocampal CA3 network

Abstract

The hippocampal CA3 region plays a key role in learning and memory. Recurrent CA3-CA3 synapses are thought to be the subcellular substrate of pattern completion. However, the synaptic mechanisms of this network computation remain enigmatic. To investigate these mechanisms, we combined functional connectivity analysis with network modeling.Simultaneous recording from up to eight CA3 pyramidal neurons revealed that connectivity was sparse, spatially uniform, and highly enriched in disynaptic motifs (reciprocal, convergence, divergence, and chain motifs). Unitary connections were comprised of one or two synaptic contacts, suggesting efficient use of postsynaptic space. Real-size modeling indicated that CA3 networks with sparse connectivity, disynaptic motifs, and single-contact connections robustly generated pattern completion. Thus, macro-and microconnectivity contribute to efficient memory storage and retrieval in hippocampal networks. 3The hippocampal CA3 region plays a key role in learning and memory (1)(2)(3)(4)(5). A hallmark property of the network is its ability to retrieve patterns from partial or noisy cues, a process referred to as autoassociative recall, attractor dynamics, or pattern completion (3-7). However, the synaptic mechanisms underlying pattern completion have remained enigmatic. Previous neuronal network models suggested that recurrent CA3-CA3 pyramidal cell synapses play a key role in this process (8)(9)(10)(11)(12)(13)(14). In the storage phase, a stimulus pattern will activate an ensemble of interconnected neurons and induce synaptic potentiation in the corresponding recurrent synapses. In the recall phase, a partial pattern will initially activate only a fraction of the ensemble, but subsequently recruit the remaining cells via potentiated synapses. Successful pattern completion requires sufficient synaptic efficacy and network connectivity (12, 14). Whether the biological properties of the CA3 network are consistent with these assumptions remains unclear. Analysis of functional connectivity in the CA3 networkThe CA3 network is often envisaged as a network of highly interconnected neurons (3-5, 8, 11). To test this hypothesis, we analyzed functional connectivity by simultaneous recordings from up to eight CA3 pyramidal neurons in rat brain in vitro, followed by selective biocytin labeling ( 4 Macroconnectivity in the CA3 networkOur results suggested that connectivity in the CA3 cell network was surprisingly sparse, with a mean connection probability of 0.92%. Both experimental data and simulations using fully reconstructed CA3 neurons labeled in vivo indicated that connectivity was only moderately dependent on slice orientation (materials and methods; fig. S3). However, connectivity may decline with distance (17).Furthermore, connectivity might be non-random, with ensembles of highly connected cells embedded in a sparsely connected population (18, 19). To test these hypotheses, we first examined whether the connection probability was dependent on intersomatic distance (Fig. 2A). The ave...

Graph Theoretic and Motif Analyses of the Hippocampal Neuron Type Potential Connectome

“…Three-node subgraphs have attracted considerable attention for their role in complex networks across disciplines (Milo et al, 2002, 2004; Shen-Orr et al, 2002), including neuroscience (Sporns and Kötter, 2004; Song et al, 2005; Santana et al, 2011; Binicewicz et al, 2015). They have been specifically studied in the hippocampus with focus directed at DG mossy cells and unidentified hilar interneurons (Larimer and Strowbridge, 2008) and among recurrent connections of CA3 pyramidal cells (Guzman et al, 2016). Building on this well-defined framework, we added excitatory/inhibitory weights and identified connectivity pattern relations among HC neuron types.…”

From the statistics of connectivity to the statistics of spike times in neuronal networks

“…Whether its predictions are consistent with new joint measurements of circuit activity and structure will be a powerful test. Significant motif cumulant structure exists in local networks of both cortex [54,55] and area CA3 of the hippocampus, where it has been suggested to play a crucial role in pattern completion [56]. This decomposition could also be used to estimate constraints on the possible functional network structures from recorded spike train correlations.…”

Neurophysiology and signaling pathways

“…It cannot be expected that memories associated with changes in specific protein molecules survive this type of molecular turnover. However, we have to consider mechanisms which can change what is initially present as a change in synaptic protein phosphorylation into a form that can last the entire life (34,35).…”

“…Normally, the activity of kinases is tightly regulated and they remain active only in the presence of a secondary messenger (35). But what if leaning changes, the kinases so that they do not need a secondary messenger any longer?…”