Reconstruction and Simulation of Neocortical Microcircuitry.

We present a first-draft digital reconstruction of the microcircuitry of somatosensory cortex of juvenile rat. The reconstruction uses cellular and synaptic organizing principles to algorithmically reconstruct detailed anatomy and physiology from sparse experimental data. An objective anatomical method defines a neocortical volume of 0.29 ± 0.01 mm(3) containing ~31,000 neurons, and patch-clamp studies identify 55 layer-specific morphological and 207 morpho-electrical neuron subtypes. When digitally reconstructed neurons are positioned in the volume and synapse formation is restricted to biological bouton densities and numbers of synapses per connection, their overlapping arbors form ~8 million connections with ~37 million synapses. Simulations reproduce an array of in vitro and in vivo experiments without parameter tuning. Additionally, we find a spectrum of network states with a sharp transition from synchronous to asynchronous activity, modulated by physiological mechanisms. The spectrum of network states, dynamically reconfigured around this transition, supports diverse information processing strategies. PAPERCLIP: VIDEO ABSTRACT.

A family of hyperpolarization-activated channels selective for protons.

Proton (H+) channels are special: They select protons against other ions that are up to a millionfold more abundant. Only a few proton channels have been identified so far. Here, we identify a family of voltage-gated "pacemaker" channels, HCNL1, that are exquisitely selective for protons. HCNL1 activates during hyperpolarization and conducts protons into the cytosol. Surprisingly, protons permeate through the channel's voltage-sensing domain, whereas the pore domain is nonfunctional. Key to proton permeation is a methionine residue that interrupts the series of regularly spaced arginine residues in the S4 voltage sensor. HCNL1 forms a tetramer and thus contains four proton pores. Unlike classic HCN channels, HCNL1 is not gated by cyclic nucleotides. The channel is present in zebrafish sperm and carries a proton inward current that acidifies the cytosol. Our results suggest that protons rather than cyclic nucleotides serve as cellular messengers in zebrafish sperm. Through small modifications in two key functional domains, HCNL1 evolutionarily adapted to a low-Na+ freshwater environment to conserve sperm's ability to depolarize.

Species-specific differences in nonlysosomal glucosylceramidase GBA2 function underlie locomotor dysfunction arising from loss-of-function mutations.

The nonlysosomal glucosylceramidase ß2 (GBA2) catalyzes the hydrolysis of glucosylceramide to glucose and ceramide. Mutations in the human GBA2 gene have been associated with hereditary spastic paraplegia (HSP), autosomal-recessive cerebellar ataxia (ARCA), and the Marinesco-Sjögren-like syndrome. However, the underlying molecular mechanisms are ill-defined. Here, using biochemistry, immunohistochemistry, structural modeling, and mouse genetics, we demonstrate that all but one of the spastic gait locus #46 (SPG46)-connected mutations cause a loss of GBA2 activity. We demonstrate that GBA2 proteins form oligomeric complexes and that protein-protein interactions are perturbed by some of these mutations. To study the pathogenesis of GBA2-related HSP and ARCA in vivo, we investigated GBA2-KO mice as a mammalian model system. However, these mice exhibited a high phenotypic variance and did not fully resemble the human phenotype, suggesting that mouse and human GBA2 differ in function. Whereas some GBA2-KO mice displayed a strong locomotor defect, others displayed only mild alterations of the gait pattern and no signs of cerebellar defects. On a cellular level, inhibition of GBA2 activity in isolated cerebellar neurons dramatically affected F-actin dynamics and reduced neurite outgrowth, which has been associated with the development of neurological disorders. Our results shed light on the molecular mechanism underlying the pathogenesis of GBA2-related HSP and ARCA and reveal species-specific differences in GBA2 function in vivo.

Post-translational cleavage of Hv1 in human sperm tunes pH- and voltage-dependent gating.

KEY POINTS: In human sperm, proton flux across the membrane is controlled by the voltage-gated proton channel Hv1. We show that sperm harbour both Hv1 and an N-terminally cleaved isoform termed Hv1Sper. The pH-control of Hv1Sper and Hv1 is distinctively different. Hv1Sper and Hv1 can form heterodimers that combine features of both constituents. Cleavage and heterodimerization of Hv1 might represent an adaptation to the specific requirements of pH control in sperm. ABSTRACT: In human sperm, the voltage-gated proton channel Hv1 controls the flux of protons across the flagellar membrane. Here, we show that sperm harbour Hv1 and a shorter isoform, termed Hv1Sper. Hv1Sper is generated from Hv1 by removal of 68 amino acids from the N-terminus by post-translational proteolytic cleavage. The pH-dependent gating of the channel isoforms is distinctly different. In both Hv1 and Hv1Sper, the conductance-voltage relationship is determined by the pH difference across the membrane (∆pH). However, simultaneous changes in intracellular and extracellular pH that leave ΔpH constant strongly shift the activation curve of Hv1Sper but not that of Hv1, demonstrating that cleavage of the N-terminus tunes pH sensing in Hv1. Moreover, we show that Hv1 and Hv1Sper assemble as heterodimers that combine features of both constituents. We suggest that cleavage and heterodimerization of Hv1 represents an adaptation to the specific requirements of pH control in sperm.

A synaptic organizing principle for cortical neuronal groups.

Neuronal circuitry is often considered a clean slate that can be dynamically and arbitrarily molded by experience. However, when we investigated synaptic connectivity in groups of pyramidal neurons in the neocortex, we found that both connectivity and synaptic weights were surprisingly predictable. Synaptic weights follow very closely the number of connections in a group of neurons, saturating after only 20% of possible connections are formed between neurons in a group. When we examined the network topology of connectivity between neurons, we found that the neurons cluster into small world networks that are not scale-free, with less than 2 degrees of separation. We found a simple clustering rule where connectivity is directly proportional to the number of common neighbors, which accounts for these small world networks and accurately predicts the connection probability between any two neurons. This pyramidal neuron network clusters into multiple groups of a few dozen neurons each. The neurons composing each group are surprisingly distributed, typically more than 100 µm apart, allowing for multiple groups to be interlaced in the same space. In summary, we discovered a synaptic organizing principle that groups neurons in a manner that is common across animals and hence, independent of individual experiences. We speculate that these elementary neuronal groups are prescribed Lego-like building blocks of perception and that acquired memory relies more on combining these elementary assemblies into higher-order constructs.

Brief bursts self-inhibit and correlate the pyramidal network.

Inhibitory pathways are an essential component in the function of the neocortical microcircuitry. Despite the relatively small fraction of inhibitory neurons in the neocortex, these neurons are strongly activated due to their high connectivity rate and the intricate manner in which they interconnect with pyramidal cells (PCs). One prominent pathway is the frequency-dependent disynaptic inhibition (FDDI) formed between layer 5 PCs and mediated by Martinotti cells (MCs). Here, we show that simultaneous short bursts in four PCs are sufficient to exert FDDI in all neighboring PCs within the dimensions of a cortical column. This powerful inhibition is mediated by few interneurons, leading to strongly correlated membrane fluctuations and synchronous spiking between PCs simultaneously receiving FDDI. Somatic integration of such inhibition is independent and electrically isolated from monosynaptic excitation formed between the same PCs. FDDI is strongly shaped by I(h) in PC dendrites, which determines the effective integration time window for inhibitory and excitatory inputs. We propose a key disynaptic mechanism by which brief bursts generated by a few PCs can synchronize the activity in the pyramidal network.

Control of intracellular pH and bicarbonate by CO2 diffusion into human sperm.

The reaction of CO2 with H2O to form bicarbonate (HCO3-) and H+ controls sperm motility and fertilization via HCO3--stimulated cAMP synthesis. A complex network of signaling proteins participates in this reaction. Here, we identify key players that regulate intracellular pH (pHi) and HCO3- in human sperm by quantitative mass spectrometry (MS) and kinetic patch-clamp fluorometry. The resting pHi is set by amiloride-sensitive Na+/H+ exchange. The sperm-specific putative Na+/H+ exchanger SLC9C1, unlike its sea urchin homologue, is not gated by voltage or cAMP. Transporters and channels implied in HCO3- transport are not detected, and may be present at copy numbers < 10 molecules/sperm cell. Instead, HCO3- is produced by diffusion of CO2 into cells and readjustment of the CO2/HCO3-/H+ equilibrium. The proton channel Hv1 may serve as a unidirectional valve that blunts the acidification ensuing from HCO3- synthesis. This work provides a new framework for the study of male infertility.

Elevator-like movements of prestin mediate outer hair cell electromotility.

The outstanding acuity of the mammalian ear relies on cochlear amplification, an active mechanism based on the electromotility (eM) of outer hair cells. eM is a piezoelectric mechanism generated by little-understood, voltage-induced conformational changes of the anion transporter homolog prestin (SLC26A5). We used a combination of molecular dynamics (MD) simulations and biophysical approaches to identify the structural dynamics of prestin that mediate eM. MD simulations showed that prestin samples a vast conformational landscape with expanded (ES) and compact (CS) states beyond previously reported prestin structures. Transition from CS to ES is dominated by the translational-rotational movement of prestin's transport domain, akin to elevator-type substrate translocation by related solute carriers. Reversible transition between CS and ES states was supported experimentally by cysteine accessibility scanning, cysteine cross-linking between transport and scaffold domains, and voltage-clamp fluorometry (VCF). Our data demonstrate that prestin's piezoelectric dynamics recapitulate essential steps of a structurally conserved ion transport cycle.

Effective stimuli for constructing reliable neuron models.

The rich dynamical nature of neurons poses major conceptual and technical challenges for unraveling their nonlinear membrane properties. Traditionally, various current waveforms have been injected at the soma to probe neuron dynamics, but the rationale for selecting specific stimuli has never been rigorously justified. The present experimental and theoretical study proposes a novel framework, inspired by learning theory, for objectively selecting the stimuli that best unravel the neuron's dynamics. The efficacy of stimuli is assessed in terms of their ability to constrain the parameter space of biophysically detailed conductance-based models that faithfully replicate the neuron's dynamics as attested by their ability to generalize well to the neuron's response to novel experimental stimuli. We used this framework to evaluate a variety of stimuli in different types of cortical neurons, ages and animals. Despite their simplicity, a set of stimuli consisting of step and ramp current pulses outperforms synaptic-like noisy stimuli in revealing the dynamics of these neurons. The general framework that we propose paves a new way for defining, evaluating and standardizing effective electrical probing of neurons and will thus lay the foundation for a much deeper understanding of the electrical nature of these highly sophisticated and non-linear devices and of the neuronal networks that they compose.

Heterogeneity in the pyramidal network of the medial prefrontal cortex.

The prefrontal cortex is specially adapted to generate persistent activity that outlasts stimuli and is resistant to distractors, presumed to be the basis of working memory. The pyramidal network that supports this activity is unknown. Multineuron patch-clamp recordings in the ferret medial prefrontal cortex showed a heterogeneity of synapses interconnecting distinct subnetworks of different pyramidal cells. One subnetwork was similar to the pyramidal network commonly found in primary sensory areas, consisting of accommodating pyramidal cells interconnected with depressing synapses. The other subnetwork contained complex pyramidal cells with dual apical dendrites displaying nonaccommodating discharge patterns; these cells were hyper-reciprocally connected with facilitating synapses displaying pronounced synaptic augmentation and post-tetanic potentiation. These cellular, synaptic and network properties could amplify recurrent interactions between pyramidal neurons and support persistent activity in the prefrontal cortex.

Voltage and pH difference across the membrane control the S4 voltage-sensor motion of the Hv1 proton channel.

The voltage-gated proton channel Hv1 is expressed in a variety of cells, including macrophages, sperm, and lung epithelial cells. Hv1 is gated by both the membrane potential and the difference between the intra- and extracellular pH (ΔpH). The coupling of voltage- and ∆pH-sensing is such that Hv1 opens only when the electrochemical proton gradient is outwardly directed. However, the molecular mechanism of this coupling is not known. Here, we investigate the coupling between voltage- and ΔpH-sensing of Ciona intestinalis proton channel (ciHv1) using patch-clamp fluorometry (PCF) and proton uncaging. We show that changes in ΔpH can induce conformational changes of the S4 voltage sensor. Our results are consistent with the idea that S4 can detect both voltage and ΔpH.

Frequency-dependent disynaptic inhibition in the pyramidal network: a ubiquitous pathway in the developing rat neocortex.

The general structure of the mammalian neocortex is remarkably similar across different cortical areas. Despite certain cytoarchitectural specializations and deviations from the general blueprint, the principal organization of the neocortex is relatively uniform. It is not known, however, to what extent stereotypic synaptic pathways resemble each other between cortical areas, and how far they might reflect possible functional uniformity or specialization. Here, we show that frequency-dependent disynaptic inhibition (FDDI) is a generic circuit motif that is present in all neocortical areas we investigated (primary somatosensory, auditory and motor cortex, secondary visual cortex and medial prefrontal cortex of the developing rat). We did find, however, area-specific differences in occurrence and kinetics of FDDI and the short-term dynamics of monosynaptic connections between pyramidal cells (PCs). Connectivity between PCs, both monosynaptic and via FDDI, is higher in primary cortices. The long-term effectiveness of FDDI is likely to be limited by an activity-dependent attenuation of the PC-interneuron synaptic transmission. Our results suggest that the basic construction of neocortical synaptic pathways follows principles that are independent of modality or hierarchical order within the neocortex.

ON selectivity in the Drosophila visual system is a multisynaptic process involving both glutamatergic and GABAergic inhibition.

Sensory systems sequentially extract increasingly complex features. ON and OFF pathways, for example, encode increases or decreases of a stimulus from a common input. This ON/OFF pathway split is thought to occur at individual synaptic connections through a sign-inverting synapse in one of the pathways. Here, we show that ON selectivity is a multisynaptic process in the Drosophila visual system. A pharmacogenetics approach demonstrates that both glutamatergic inhibition through GluClα and GABAergic inhibition through Rdl mediate ON responses. Although neurons postsynaptic to the glutamatergic ON pathway input L1 lose all responses in GluClα mutants, they are resistant to a cell-type-specific loss of GluClα. This shows that ON selectivity is distributed across multiple synapses, and raises the possibility that cell-type-specific manipulations might reveal similar strategies in other sensory systems. Thus, sensory coding is more distributed than predicted by simple circuit motifs, allowing for robust neural processing.

Inferring connection proximity in networks of electrically coupled cells by subthreshold frequency response analysis.

Electrical synapses continuously transfer signals bi-directionally from one cell to another, directly or indirectly via intermediate cells. Electrical synapses are common in many brain structures such as the inferior olive, the subcoeruleus nucleus and the neocortex, between neurons and between glial cells. In the cortex, interneurons have been shown to be electrically coupled and proposed to participate in large, continuous cortical syncytia, as opposed to smaller spatial domains of electrically coupled cells. However, to explore the significance of these findings it is imperative to map the electrical synaptic microcircuits, in analogy with in vitro studies on monosynaptic and disynaptic chemical coupling. Since "walking" from cell to cell over large distances with a glass pipette is challenging, microinjection of (fluorescent) dyes diffusing through gap-junctions remains so far the only method available to decipher such microcircuits even though technical limitations exist. Based on circuit theory, we derive analytical descriptions of the AC electrical coupling in networks of isopotential cells. We then suggest an operative electrophysiological protocol to distinguish between direct electrical connections and connections involving one or more intermediate cells. This method allows inferring the number of intermediate cells, generalizing the conventional coupling coefficient, which provides limited information. We validate our method through computer simulations, theoretical and numerical methods and electrophysiological paired recordings.

Evaluating automated parameter constraining procedures of neuron models by experimental and surrogate data.

Neuron models, in particular conductance-based compartmental models, often have numerous parameters that cannot be directly determined experimentally and must be constrained by an optimization procedure. A common practice in evaluating the utility of such procedures is using a previously developed model to generate surrogate data (e.g., traces of spikes following step current pulses) and then challenging the algorithm to recover the original parameters (e.g., the value of maximal ion channel conductances) that were used to generate the data. In this fashion, the success or failure of the model fitting procedure to find the original parameters can be easily determined. Here we show that some model fitting procedures that provide an excellent fit in the case of such model-to-model comparisons provide ill-balanced results when applied to experimental data. The main reason is that surrogate and experimental data test different aspects of the algorithm's function. When considering model-generated surrogate data, the algorithm is required to locate a perfect solution that is known to exist. In contrast, when considering experimental target data, there is no guarantee that a perfect solution is part of the search space. In this case, the optimization procedure must rank all imperfect approximations and ultimately select the best approximation. This aspect is not tested at all when considering surrogate data since at least one perfect solution is known to exist (the original parameters) making all approximations unnecessary. Furthermore, we demonstrate that distance functions based on extracting a set of features from the target data (such as time-to-first-spike, spike width, spike frequency, etc.)--rather than using the original data (e.g., the whole spike trace) as the target for fitting-are capable of finding imperfect solutions that are good approximations of the experimental data.

The quantitative single-neuron modeling competition.

As large-scale, detailed network modeling projects are flourishing in the field of computational neuroscience, it is more and more important to design single neuron models that not only capture qualitative features of real neurons but are quantitatively accurate in silico representations of those. Recent years have seen substantial effort being put in the development of algorithms for the systematic evaluation and optimization of neuron models with respect to electrophysiological data. It is however difficult to compare these methods because of the lack of appropriate benchmark tests. Here, we describe one such effort of providing the community with a standardized set of tests to quantify the performances of single neuron models. Our effort takes the form of a yearly challenge similar to the ones which have been present in the machine learning community for some time. This paper gives an account of the first two challenges which took place in 2007 and 2008 and discusses future directions. The results of the competition suggest that best performance on data obtained from single or double electrode current or conductance injection is achieved by models that combine features of standard leaky integrate-and-fire models with a second variable reflecting adaptation, refractoriness, or a dynamic threshold.

Extracting non-linear integrate-and-fire models from experimental data using dynamic I-V curves.

The dynamic I-V curve method was recently introduced for the efficient experimental generation of reduced neuron models. The method extracts the response properties of a neuron while it is subject to a naturalistic stimulus that mimics in vivo-like fluctuating synaptic drive. The resulting history-dependent, transmembrane current is then projected onto a one-dimensional current-voltage relation that provides the basis for a tractable non-linear integrate-and-fire model. An attractive feature of the method is that it can be used in spike-triggered mode to quantify the distinct patterns of post-spike refractoriness seen in different classes of cortical neuron. The method is first illustrated using a conductance-based model and is then applied experimentally to generate reduced models of cortical layer-5 pyramidal cells and interneurons, in injected-current and injected- conductance protocols. The resulting low-dimensional neuron models-of the refractory exponential integrate-and-fire type-provide highly accurate predictions for spike-times. The method therefore provides a useful tool for the construction of tractable models and rapid experimental classification of cortical neurons.

A novel cross-species inhibitor to study the function of CatSper Ca2+ channels in sperm.

BACKGROUND AND PURPOSE: Sperm from many species share the sperm-specific Ca2+ channel CatSper that controls the intracellular Ca2+ concentration and, thereby, the swimming behaviour. A growing body of evidence suggests that the mechanisms controlling the activity of CatSper and its role during fertilization differ among species. A lack of suitable pharmacological tools has hampered the elucidation of the function of CatSper. Known inhibitors of CatSper exhibit considerable side effects and also inhibit Slo3, the principal K+ channel of mammalian sperm. The compound RU1968 was reported to suppress Ca2+ signaling in human sperm by an unknown mechanism. Here, we examined the action of RU1968 on CatSper in sperm from humans, mice, and sea urchins. EXPERIMENTAL APPROACH: We resynthesized RU1968 and studied its action on sperm from humans, mice, and the sea urchin Arbacia punctulata by Ca2+ fluorimetry, single-cell Ca2+ imaging, electrophysiology, opto-chemistry, and motility analysis. KEY RESULTS: RU1968 inhibited CatSper in sperm from invertebrates and mammals. The compound lacked toxic side effects in human sperm, did not affect mouse Slo3, and inhibited human Slo3 with about 15-fold lower potency than CatSper. Moreover, in human sperm, RU1968 mimicked CatSper dysfunction and suppressed motility responses evoked by progesterone, an oviductal steroid known to activate CatSper. Finally, RU1968 abolished CatSper-mediated chemotactic navigation in sea urchin sperm. CONCLUSION AND IMPLICATIONS: We propose RU1968 as a novel tool to elucidate the function of CatSper channels in sperm across species.

Photocontrol of the Hv1 Proton Channel.

The voltage-gated proton channel Hv1 is expressed in various human cell types, including macrophages, epithelial cells, and sperm. Hv1 opening leads to proton efflux that alkalizes the cytosol. Here, we describe light-activated Hv1 inhibitors (photoswitches) that allow controlling its activity with high spatiotemporal precision. The photoswitches comprise a light-sensitive azobenzene moiety and 2-guanidinobenzimidazole (2GBI), a known Hv1 inhibitor. In the dark, photoGBI inhibits heterologously expressed Hv1 channels. Blue light, which isomerizes the azobenzene group from trans to cis conformation, releases inhibition. We demonstrate photocontrol of native proton currents in human macrophages and sperm using photoGBI, underlining their use as valuable optochemical tools to study the function of Hv1 channels.

Fluorescent labeling for patch-clamp fluorometry (PCF) measurements of real-time protein motion in ion channels.

Understanding the function of ion channels is a major goal of molecular neurophysiology. While standard electrophysiological methods are invaluable tools to investigate the gating of ion channels, the structural rearrangements that mediate the way a channel senses physiological signals and opens and closes its gates cannot be measured electrically in a direct way. Here, we describe a method, based on site-specific labeling of a channel of interest with an environmentally sensitive fluorophore, which makes it possible to monitor conformational changes of ion channels in biological membranes in real time.