NMDAR-mediated activation of pannexin1 channels contributes to the detonator properties of hippocampal mossy fiber synapses.

Pannexins are large-pore ion channels expressed throughout the mammalian brain that participate in various neuropathologies; however, their physiological roles remain obscure. Here, we report that pannexin1 channels (Panx1) can be synaptically activated under physiological recording conditions in rodent acute hippocampal slices. Specifically, NMDA receptor (NMDAR)-mediated responses at the mossy fiber to CA3 pyramidal cell synapse were followed by a slow postsynaptic inward current that could activate CA3 pyramidal cells but was absent in Panx1 knockout mice. Immunoelectron microscopy revealed that Panx1 was localized near the postsynaptic density. Further, Panx1-mediated currents were potentiated by metabotropic receptors and bidirectionally modulated by burst-timing-dependent plasticity of NMDAR-mediated transmission. Lastly, Panx1 channels were preferentially recruited when NMDAR activation enters a supralinear regime, resulting in temporally delayed burst-firing. Thus, Panx1 can contribute to synaptic amplification and broadening the temporal associativity window for co-activated pyramidal cells, thereby supporting the auto-associative functions of the CA3 region.

Cell type-specific mechanisms of information transfer in data-driven biophysical models of hippocampal CA3 principal neurons.

The transformation of synaptic input into action potential output is a fundamental single-cell computation resulting from the complex interaction of distinct cellular morphology and the unique expression profile of ion channels that define the cellular phenotype. Experimental studies aimed at uncovering the mechanisms of the transfer function have led to important insights, yet are limited in scope by technical feasibility, making biophysical simulations an attractive complementary approach to push the boundaries in our understanding of cellular computation. Here we take a data-driven approach by utilizing high-resolution morphological reconstructions and patch-clamp electrophysiology data together with a multi-objective optimization algorithm to build two populations of biophysically detailed models of murine hippocampal CA3 pyramidal neurons based on the two principal cell types that comprise this region. We evaluated the performance of these models and find that our approach quantitatively matches the cell type-specific firing phenotypes and recapitulate the intrinsic population-level variability in the data. Moreover, we confirm that the conductance values found by the optimization algorithm are consistent with differentially expressed ion channel genes in single-cell transcriptomic data for the two cell types. We then use these models to investigate the cell type-specific biophysical properties involved in the generation of complex-spiking output driven by synaptic input through an information-theoretic treatment of their respective transfer functions. Our simulations identify a host of cell type-specific biophysical mechanisms that define the morpho-functional phenotype to shape the cellular transfer function and place these findings in the context of a role for bursting in CA3 recurrent network synchronization dynamics.

Retrograde Suppression of Post-Tetanic Potentiation at the Mossy Fiber-CA3 Pyramidal Cell Synapse.

In the hippocampus, the excitatory synapse between dentate granule cell (GC) axons, or mossy fibers (MFs), and CA3 pyramidal cells (MF-CA3) expresses robust forms of short-term plasticity, such as frequency facilitation and post-tetanic potentiation (PTP). These forms of plasticity are due to increases in presynaptic neurotransmitter release, and can be engaged when dentate GCs fire in bursts (e.g., during exploratory behaviors) and bring CA3 pyramidal neurons above threshold. While frequency facilitation at this synapse is limited by endogenous activation of presynaptic metabotropic glutamate receptors (mGluRs), whether MF-PTP can be regulated in an activity-dependent manner is unknown. Here, using physiologically relevant patterns of MF stimulation in acute mouse hippocampal slices, we found that disrupting postsynaptic Ca2+ dynamics increases MF-PTP, strongly suggesting a form of Ca2+-dependent retrograde suppression of this form of plasticity. PTP suppression requires a few seconds of MF bursting activity and Ca2+ release from internal stores. Our findings raise the possibility that the powerful MF-CA3 synapse can negatively regulate its own strength not only during PTP-inducing activity typical of normal exploratory behaviors, but also during epileptic activity.

ShuTu: Open-Source Software for Efficient and Accurate Reconstruction of Dendritic Morphology.

Neurons perform computations by integrating inputs from thousands of synapses-mostly in the dendritic tree-to drive action potential firing in the axon. One fruitful approach to studying this process is to record from neurons using patch-clamp electrodes, fill the recorded neurons with a substance that allows subsequent staining, reconstruct the three-dimensional architectures of the dendrites, and use the resulting functional and structural data to develop computer models of dendritic integration. Accurately producing quantitative reconstructions of dendrites is typically a tedious process taking many hours of manual inspection and measurement. Here we present ShuTu, a new software package that facilitates accurate and efficient reconstruction of dendrites imaged using bright-field microscopy. The program operates in two steps: (1) automated identification of dendritic processes, and (2) manual correction of errors in the automated reconstruction. This approach allows neurons with complex dendritic morphologies to be reconstructed rapidly and efficiently, thus facilitating the use of computer models to study dendritic structure-function relationships and the computations performed by single neurons.

Revealing the Synaptic Hodology of Mammalian Neural Circuits With Multiscale Neurocartography.

The functional features of neural circuits are determined by a combination of properties that range in scale from projections systems across the whole brain to molecular interactions at the synapse. The burgeoning field of neurocartography seeks to map these relevant features of brain structure-spanning a volume ∼20 orders of magnitude-to determine how neural circuits perform computations supporting cognitive function and complex behavior. Recent technological breakthroughs in tissue sample preparation, high-throughput electron microscopy imaging, and automated image analyses have produced the first visualizations of all synaptic connections between neurons of invertebrate model systems. However, the sheer size of the central nervous system in mammals implies that reconstruction of the first full brain maps at synaptic scale may not be feasible for decades. In this review, we outline existing and emerging technologies for neurocartography that complement electron microscopy-based strategies and are beginning to derive some basic organizing principles of circuit hodology at the mesoscale, microscale, and nanoscale. Specifically, we discuss how a host of light microscopy techniques including array tomography have been utilized to determine both long-range and subcellular organizing principles of synaptic connectivity. In addition, we discuss how new techniques, such as two-photon serial tomography of the entire mouse brain, have become attractive approaches to dissect the potential connectivity of defined cell types. Ultimately, principles derived from these techniques promise to facilitate a conceptual understanding of how connectomes, and neurocartography in general, can be effectively utilized toward reaching a mechanistic understanding of circuit function.

Multimodal in vivo brain electrophysiology with integrated glass microelectrodes.

Electrophysiology is the most used approach for the collection of functional data in basic and translational neuroscience, but it is typically limited to either intracellular or extracellular recordings. The integration of multiple physiological modalities for the routine acquisition of multimodal data with microelectrodes could be useful for biomedical applications, yet this has been challenging owing to incompatibilities of fabrication methods. Here, we present a suite of glass pipettes with integrated microelectrodes for the simultaneous acquisition of multimodal intracellular and extracellular information in vivo, electrochemistry assessments, and optogenetic perturbations of neural activity. We used the integrated devices to acquire multimodal signals from the CA1 region of the hippocampus in mice and rats, and show that these data can serve as ground-truth validation for the performance of spike-sorting algorithms. The microdevices are applicable for basic and translational neurobiology, and for the development of next-generation brain-machine interfaces.

Mapping the transcriptional diversity of genetically and anatomically defined cell populations in the mouse brain.

Understanding the principles governing neuronal diversity is a fundamental goal for neuroscience. Here, we provide an anatomical and transcriptomic database of nearly 200 genetically identified cell populations. By separately analyzing the robustness and pattern of expression differences across these cell populations, we identify two gene classes contributing distinctly to neuronal diversity. Short homeobox transcription factors distinguish neuronal populations combinatorially, and exhibit extremely low transcriptional noise, enabling highly robust expression differences. Long neuronal effector genes, such as channels and cell adhesion molecules, contribute disproportionately to neuronal diversity, based on their patterns rather than robustness of expression differences. By linking transcriptional identity to genetic strains and anatomical atlases, we provide an extensive resource for further investigation of mouse neuronal cell types.

A novel pyramidal cell type promotes sharp-wave synchronization in the hippocampus.

To support cognitive function, the CA3 region of the hippocampus performs computations involving attractor dynamics. Understanding how cellular and ensemble activities of CA3 neurons enable computation is critical for elucidating the neural correlates of cognition. Here we show that CA3 comprises not only classically described pyramid cells with thorny excrescences, but also includes previously unidentified 'athorny' pyramid cells that lack mossy-fiber input. Moreover, the two neuron types have distinct morphological and physiological phenotypes and are differentially modulated by acetylcholine. To understand the contribution of these athorny pyramid neurons to circuit function, we measured cell-type-specific firing patterns during sharp-wave synchronization events in vivo and recapitulated these dynamics with an attractor network model comprising two principal cell types. Our data and simulations reveal a key role for athorny cell bursting in the initiation of sharp waves: transient network attractor states that signify the execution of pattern completion computations vital to cognitive function.

Bidirectional NMDA receptor plasticity controls CA3 output and heterosynaptic metaplasticity.

NMDA receptors (NMDARs) are classically known as coincidence detectors for the induction of long-term synaptic plasticity and have been implicated in hippocampal CA3 cell-dependent spatial memory functions that likely rely on dynamic cellular ensemble encoding of space. The unique functional properties of both NMDARs and mossy fiber projections to CA3 pyramidal cells place mossy fiber NMDARs in a prime position to influence CA3 ensemble dynamics. By mimicking presynaptic and postsynaptic activity patterns observed in vivo, we found a burst timing-dependent pattern of activity that triggered bidirectional long-term NMDAR plasticity at mossy fiber-CA3 synapses in rat hippocampal slices. This form of plasticity imparts bimodal control of mossy fiber-driven CA3 burst firing and spike temporal fidelity. Moreover, we found that mossy fiber NMDARs mediate heterosynaptic metaplasticity between mossy fiber and associational-commissural synapses. Thus, bidirectional NMDAR plasticity at mossy fiber-CA3 synapses could substantially contribute to the formation, storage and recall of CA3 cell assembly patterns.

Synaptic plasticity of NMDA receptors: mechanisms and functional implications.

Beyond their well-established role as triggers for LTP and LTD of fast synaptic transmission mediated by AMPA receptors, an expanding body of evidence indicates that NMDA receptors (NMDARs) themselves are also dynamically regulated and subject to activity-dependent long-term plasticity. NMDARs can significantly contribute to information transfer at synapses particularly during periods of repetitive activity. It is also increasingly recognized that NMDARs participate in dendritic synaptic integration and are critical for generating persistent activity of neural assemblies. Here we review recent advances on the mechanisms and functional consequences of NMDAR plasticity. Given the unique biophysical properties of NMDARs, synaptic plasticity of NMDAR-mediated transmission emerges as a particularly powerful mechanism for the fine tuning of information encoding and storage throughout the brain.

Distinct functions of kainate receptors in the brain are determined by the auxiliary subunit Neto1.

Ionotropic glutamate receptors principally mediate fast excitatory transmission in the brain. Among the three classes of ionotropic glutamate receptors, kainate receptors (KARs) have a unique brain distribution, which has been historically defined by (3)H-radiolabeled kainate binding. Compared with recombinant KARs expressed in heterologous cells, synaptic KARs exhibit characteristically slow rise-time and decay kinetics. However, the mechanisms responsible for these distinct KAR properties remain unclear. We found that both the high-affinity binding pattern in the mouse brain and the channel properties of native KARs are determined by the KAR auxiliary subunit Neto1. Through modulation of agonist binding affinity and off-kinetics of KARs, but not trafficking of KARs, Neto1 determined both the KAR high-affinity binding pattern and the distinctively slow kinetics of postsynaptic KARs. By regulating KAR excitatory postsynaptic current kinetics, Neto1 can control synaptic temporal summation, spike generation and fidelity.

Automated Lead Optimization of MMP-12 Inhibitors Using a Genetic Algorithm.

Traditional lead optimization projects involve long synthesis and testing cycles, favoring extensive structure-activity relationship (SAR) analysis and molecular design steps, in an attempt to limit the number of cycles that a project must run to optimize a development candidate. Microfluidic-based chemistry and biology platforms, with cycle times of minutes rather than weeks, lend themselves to unattended autonomous operation. The bottleneck in the lead optimization process is therefore shifted from synthesis or test to SAR analysis and design. As such, the way is open to an algorithm-directed process, without the need for detailed user data analysis. Here, we present results of two synthesis and screening experiments, undertaken using traditional methodology, to validate a genetic algorithm optimization process for future application to a microfluidic system. The algorithm has several novel features that are important for the intended application. For example, it is robust to missing data and can suggest compounds for retest to ensure reliability of optimization. The algorithm is first validated on a retrospective analysis of an in-house library embedded in a larger virtual array of presumed inactive compounds. In a second, prospective experiment with MMP-12 as the target protein, 140 compounds are submitted for synthesis over 10 cycles of optimization. Comparison is made to the results from the full combinatorial library that was synthesized manually and tested independently. The results show that compounds selected by the algorithm are heavily biased toward the more active regions of the library, while the algorithm is robust to both missing data (compounds where synthesis failed) and inactive compounds. This publication places the full combinatorial library and biological data into the public domain with the intention of advancing research into algorithm-directed lead optimization methods.