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...

CA3–CA3 recurrent excitatory synapses are thought to play a key role in memory storage and pattern completion. Whether the plasticity properties of these synapses are consistent with their proposed network functions remains unclear. Here, we examine the properties of spike timing-dependent plasticity (STDP) at CA3–CA3 synapses. Low-frequency pairing of excitatory postsynaptic potentials (EPSPs) and action potentials (APs) induces long-term potentiation (LTP), independent of temporal order. The STDP curve is symmetric and broad (half-width ∼150 ms). Consistent with these STDP induction properties, AP–EPSP sequences lead to supralinear summation of spine [Ca2+] transients. Furthermore, afterdepolarizations (ADPs) following APs efficiently propagate into dendrites of CA3 pyramidal neurons, and EPSPs summate with dendritic ADPs. In autoassociative network models, storage and recall are more robust with symmetric than with asymmetric STDP rules. Thus, a specialized STDP induction rule allows reliable storage and recall of information in the hippocampal CA3 network.

Parvalbumin-positive (PV+) GABAergic interneurons in hippocampal microcircuits are thought to play a key role in several higher network functions, such as feedforward and feedback inhibition, network oscillations, and pattern separation. Fast lateral inhibition mediated by GABAergic interneurons may implement a winner-takes-all mechanism in the hippocampal input layer. However, it is not clear whether the functional connectivity rules of granule cells (GCs) and interneurons in the dentate gyrus are consistent with such a mechanism. Using simultaneous patch-clamp recordings from up to seven GCs and up to four PV+ interneurons in the dentate gyrus, we find that connectivity is structured in space, synapse-specific, and enriched in specific disynaptic motifs. In contrast to the neocortex, lateral inhibition in the dentate gyrus (in which a GC inhibits neighboring GCs via a PV+ interneuron) is ~ 10-times more abundant than recurrent inhibition (in which a GC inhibits itself). Thus, unique connectivity rules may enable the dentate gyrus to perform specific higher-order computations.

CA3 pyramidal neurons are important for memory formation and pattern completion in the hippocampal network. It is generally thought that proximal synapses from the mossy fibers activate these neurons most efficiently, whereas distal inputs from the perforant path have a weaker modulatory influence. We used confocally targeted patch-clamp recording from dendrites and axons to map the activation of rat CA3 pyramidal neurons at the subcellular level. Our results reveal two distinct dendritic domains. In the proximal domain, action potentials initiated in the axon backpropagate actively with large amplitude and fast time course. In the distal domain, Na + channel-mediated dendritic spikes are efficiently initiated by waveforms mimicking synaptic events. CA3 pyramidal neuron dendrites showed a high Na + -to-K + conductance density ratio, providing ideal conditions for active backpropagation and dendritic spike initiation. Dendritic spikes may enhance the computational power of CA3 pyramidal neurons in the hippocampal network.CA3 pyramidal neurons in the hippocampal network are critical for spatial information processing and memory 1-5 . These neurons receive three different glutamatergic inputs. Proximal mossy fiber synapses activate CA3 cells efficiently, acting as 'conditional detonators' 6,7 . Commissural/associational synapses between CA3 cells are thought to store memories by spike timing-dependent plasticity, but whether backpropagated action potentials efficiently invade the postsynaptic dendrites in CA3 pyramidal neurons is unclear [8][9][10] . Distal perforant path synapses from the entorhinal cortex may relay information about context 2 , but how synaptic signals are conducted to the soma via the long dendritic cable has not been resolved. Recent results have suggested that most entorhinal cortex layer 2 pyramidal neurons are grid cells 11 , indicating that perforant path inputs may signal precise spatiotemporal information. How this information is processed by CA3 pyramidal cell dendrites remains unclear.To understand both the induction rules of synaptic plasticity and the efficacy of distal inputs in CA3 pyramidal neurons, knowledge about the properties of the dendrites of these neurons is essential. Highly detailed information is available about the dendrites of layer 5 pyramidal cells in the neocortex and CA1 pyramidal neurons in the hippocampus 12-15 (reviewed by ref. 16). In contrast, both the difficulty of maintaining CA3 pyramidal cells in in vitro slice preparations and the small caliber of the dendritic processes of these cells have prevented a detailed analysis by direct recordings. Recent experiments using glutamate uncaging have

Intracellular electrophysiological recordings provide crucial insights into elementary neuronal signals such as action potentials and synaptic currents. Analyzing and interpreting these signals is essential for a quantitative understanding of neuronal information processing, and requires both fast data visualization and ready access to complex analysis routines. To achieve this goal, we have developed Stimfit, a free software package for cellular neurophysiology with a Python scripting interface and a built-in Python shell. The program supports most standard file formats for cellular neurophysiology and other biomedical signals through the Biosig library. To quantify and interpret the activity of single neurons and communication between neurons, the program includes algorithms to characterize the kinetics of presynaptic action potentials and postsynaptic currents, estimate latencies between pre- and postsynaptic events, and detect spontaneously occurring events. We validate and benchmark these algorithms, give estimation errors, and provide sample use cases, showing that Stimfit represents an efficient, accessible and extensible way to accurately analyze and interpret neuronal signals.

ATP released from neurons and astrocytes during neuronal activity or under pathophysiological circumstances is able to influence information flow in neuronal circuits by activation of ionotropic P2X and metabotropic P2Y receptors and subsequent modulation of cellular excitability, synaptic strength, and plasticity. In the present paper we review cellular and network effects of P2Y receptors in the brain. We show that P2Y receptors inhibit the release of neurotransmitters, modulate voltage- and ligand-gated ion channels, and differentially influence the induction of synaptic plasticity in the prefrontal cortex, hippocampus, and cerebellum. The findings discussed here may explain how P2Y1 receptor activation during brain injury, hypoxia, inflammation, schizophrenia, or Alzheimer's disease leads to an impairment of cognitive processes. Hence, it is suggested that the blockade of P2Y1 receptors may have therapeutic potential against cognitive disturbances in these states.

Current responses to N-methyl-D-aspartate (NMDA) in layer V pyramidal neurons of the rat prefrontal cortex were potentiated by the P2 receptor agonists adenosine 5'-triphosphate (ATP) and uridine 5'-triphosphate (UTP). The failure of these nucleotides to induce inward current on fast local superfusion suggested the activation of P2Y rather than P2X receptors. The potentiation by ATP persisted in a Ca(2+)-free superfusion medium but was abolished by 1,2-bis(2-amino-5-fluorophenoxy)ethane-N,N,N',N'-tetraacetic acid tetrakis(acetoxymethyl) ester, cyclopiazonic acid, 7-nitroindazole, fluoroacetic acid, bafilomycin, and tetanus toxin, indicating that an astrocytic signaling molecule may participate. Because the metabotropic glutamate receptor (mGluR) agonists (1S,3R)-1-aminocyclopentane-1,3-dicarboxylic acid (ACPD) (group I/II) and (RS)-3,5-dihydroxyphenylglycine (group I) both imitated the effect of ATP and the group I mGluR antagonist 1-aminoindan-1,5-dicarboxylic acid or a combination of selective mGluR(1) (7-(hydroxyimino)-cyclopropa[b]chromen-1a-carboxylate) and mGluR(5) (2-methyl-6-(phenylethynyl)pyridine) antagonists abolished the facilitation by ATP, it was concluded that the signaling molecule may be glutamate. Pharmacological tools known to interfere with the transduction cascade of type I mGluRs (guanosine 5'-O-(3-thiodiphosphate), U-73122, xestospongin C, 1,2-bis(2-aminophenoxy)ethane-N,N,N',N'-tetraacetic acid, calmodulin kinase II [CAMKII] inhibitor peptide) depressed the actions of both ATP and ACPD. Characterization of the P2Y receptor by agonists (ATP and UTP), antagonists (suramin and pyridoxal-phosphate-6-azophenyl-2',4'-disulfonic acid), and knockout mice (P2Y(2)(-/-)) suggested that the nucleotides act at the P2Y(4) subtype. In conclusion, we propose that exogenous and probably also endogenous ATP release vesicular glutamate from astrocytes by P2Y(4) receptor activation. This glutamate then stimulates type I mGluRs of layer V pyramidal neurons and via the G(q)/phospholipase C/inositol 1,4,5-trisphosphate/Ca(2+)/CAMKII transduction pathway facilitates NMDA receptor currents.

Pattern separation is a fundamental brain computation that converts small differences in synaptic input patterns into large differences in action potential (AP) output patterns. Pattern separation plays a key role in the dentate gyrus, enabling the efficient storage and recall of memories in downstream hippocampal CA3 networks. Several mechanisms for pattern separation have been proposed, including expansion of coding space, sparsification of neuronal activity, and simple thresholding mechanisms. Alternatively, a winner-takes-all mechanism, in which the most excited cells inhibit all less-excited cells by lateral inhibition, might be involved. Although such a mechanism is computationally powerful, it remains unclear whether it operates in biological networks. Here, we develop a full-scale network model of the dentate gyrus, comprised of granule cells (GCs) and parvalbumin + (PV + ) inhibitory interneurons, based on experimentally determined biophysical cellular properties and synaptic connectivity rules. Our results demonstrate that a biologically realistic principal neuron-interneuron (PN-IN) network model is a highly efficient pattern separator. Mechanistic dissection in the model revealed that a winner-takes-all mechanism by lateral inhibition plays a crucial role in pattern separation. Furthermore, both fast signaling properties of PV + interneurons and focal GC-interneuron connectivity are essential for efficient pattern separation. Thus, PV + interneurons are not only involved in basic microcircuit functions, but also contribute to higher-order computations in neuronal networks, such as pattern separation.