William L. Kath

Factors mediating powerful voltage attenuation along CA1 pyramidal neuron dendrites.

We performed simultaneous patch‐electrode recordings from the soma and apical dendrite of CA1 pyramidal neurons in hippocampal slices, in order to determine the degree of voltage attenuation along CA1 dendrites. Fifty per cent attenuation of steady‐state somatic voltage changes occurred at a distance of 238 μm from the soma in control and 409 μm after blocking the hyperpolarization‐activated (H) conductance. The morphology of three neurons was reconstructed and used to generate computer models, which were adjusted to fit the somatic and dendritic voltage responses. These models identify several factors contributing to the voltage attenuation along CA1 dendrites, including high axial cytoplasmic resistivity, low membrane resistivity, and large H conductance. In most cells the resting membrane conductances, including the H conductances, were larger in the dendrites than the soma. Simulations suggest that synaptic potentials attenuate enormously as they propagate from the dendrite to the soma, with greater than 100‐fold attenuation for synapses on many small, distal dendrites. A prediction of this powerful EPSP attenuation is that distal synaptic inputs are likely only to be effective in the presence of conductance scaling, dendritic excitability, or both.

Synaptic amplification by dendritic spines enhances input cooperativity

Dendritic spines are the nearly ubiquitous site of excitatory synaptic input onto neurons and as such are critically positioned to influence diverse aspects of neuronal signalling. Decades of theoretical studies have proposed that spines may function as highly effective and modifiable chemical and electrical compartments that regulate synaptic efficacy, integration and plasticity. Experimental studies have confirmed activity-dependent structural dynamics and biochemical compartmentalization by spines. However, there is a longstanding debate over the influence of spines on the electrical aspects of synaptic transmission and dendritic operation. Here we measure the amplitude ratio of spine head to parent dendrite voltage across a range of dendritic compartments and calculate the associated spine neck resistance (Rneck) for spines at apical trunk dendrites in rat hippocampal CA1 pyramidal neurons. We find that Rneck is large enough (∼500 MΩ) to amplify substantially the spine head depolarization associated with a unitary synaptic input by ∼1.5- to ∼45-fold, depending on parent dendritic impedance. A morphologically realistic compartmental model capable of reproducing the observed spatial profile of the amplitude ratio indicates that spines provide a consistently high-impedance input structure throughout the dendritic arborization. Finally, we demonstrate that the amplification produced by spines encourages electrical interaction among coactive inputs through an Rneck-dependent increase in spine head voltage-gated conductance activation. We conclude that the electrical properties of spines promote nonlinear dendritic processing and associated forms of plasticity and storage, thus fundamentally enhancing the computational capabilities of neurons.

Accurate calculation of eye diagrams and bit error rates in optical transmission systems using linearization

We present a novel linearization method to calculate accurate eye diagrams and bit error rates (BERs) for arbitrary optical transmission systems and apply it to a dispersion-managed soliton (DMS) system. In this approach, we calculate the full nonlinear evolution using Monte Carlo methods. However, we analyze the data at the receiver assuming that the nonlinear interaction of the noise with itself in an appropriate basis set is negligible during transmission. Noise-noise beating due to the quadratic nonlinearity in the receiver is kept. We apply this approach to a highly nonlinear DMS system, which is a stringent test of our approach. In this case, we cannot simply use a Fourier basis to linearize, but we must first separate the phase and timing jitters. Once that is done, the remaining Fourier amplitudes of the noise obey a multivariate Gaussian distribution, the timing jitter is Gaussian distributed, and the phase jitter obeys a Jacobi-/spl Theta/ distribution, which is the periodic analogue of a Gaussian distribution. We have carefully validated the linearization assumption through extensive Monte Carlo simulations. Once the effect of timing jitter is restored at the receiver, we calculate complete eye diagrams and the probability density functions for the marks and spaces. This new method is far more accurate than the currently accepted approach of simply fitting Gaussian curves to the distributions of the marks and spaces. In addition, we present a deterministic solution alternative to the Monte Carlo method.

Realistic control of network dynamics

The control of complex networks is of paramount importance in areas as diverse as ecosystem management, emergency response and cell reprogramming. A fundamental property of networks is that perturbations to one node can affect other nodes, potentially causing the entire system to change behaviour or fail. Here we show that it is possible to exploit the same principle to control network behaviour. Our approach accounts for the nonlinear dynamics inherent to real systems, and allows bringing the system to a desired target state even when this state is not directly accessible due to constraints that limit the allowed interventions. Applications show that this framework permits reprogramming a network to a desired task, as well as rescuing networks from the brink of failure-which we illustrate through the mitigation of cascading failures in a power-grid network and the identification of potential drug targets in a signalling network of human cancer.

Distance-Dependent Differences in Synapse Number and AMPA Receptor Expression in Hippocampal CA1 Pyramidal Neurons

The ability of synapses throughout the dendritic tree to influence neuronal output is crucial for information processing in the brain. Synaptic potentials attenuate dramatically, however, as they propagate along dendrites toward the soma. To examine whether excitatory axospinous synapses on CA1 pyramidal neurons compensate for their distance from the soma to counteract such dendritic filtering, we evaluated axospinous synapse number and receptor expression in three progressively distal regions: proximal and distal stratum radiatum (SR), and stratum lacunosum-moleculare (SLM). We found that the proportion of perforated synapses increases as a function of distance from the soma and that their AMPAR, but not NMDAR, expression is highest in distal SR and lowest in SLM. Computational models of pyramidal neurons derived from these results suggest that they arise from the compartment-specific use of conductance scaling in SR and dendritic spikes in SLM to minimize the influence of distance on synaptic efficacy.

Synapse distribution suggests a two-stage model of dendritic integration in CA1 pyramidal neurons.

Competing models have been proposed to explain how neurons integrate the thousands of inputs distributed throughout their dendritic trees. In a simple global integration model, inputs from all locations sum in the axon. In a two-stage integration model, inputs contribute directly to dendritic spikes, and outputs from multiple branches sum in the axon. These two models yield opposite predictions of how synapses at different dendritic locations should be scaled if they are to contribute equally to neuronal output. We used serial-section electron microscopy to reconstruct individual apical oblique dendritic branches of CA1 pyramidal neurons and observe a synapse distribution consistent with the two-stage integration model. Computational modeling suggests that the observed synapse distribution enhances the contribution of each dendritic branch to neuronal output.

Hippocampal pyramidal neurons comprise two distinct cell types that are countermodulated by metabotropic receptors.

Relating the function of neuronal cell types to information processing and behavior is a central goal of neuroscience. In the hippocampus, pyramidal cells in CA1 and the subiculum process sensory and motor cues to form a cognitive map encoding spatial, contextual, and emotional information, which they transmit throughout the brain. Do these cells constitute a single class or are there multiple cell types with specialized functions? Using unbiased cluster analysis, we show that there are two morphologically and electrophysiologically distinct principal cell types that carry hippocampal output. We show further that these two cell types are inversely modulated by the synergistic action of glutamate and acetylcholine acting on metabotropic receptors that are central to hippocampal function. Combined with prior connectivity studies, our results support a model of hippocampal processing in which the two pyramidal cell types are predominantly segregated into two parallel pathways that process distinct modalities of information.Relating the function of neuronal cell types to information processing and behavior is a central goal of neuroscience. In the hippocampus, pyramidal cells in CA1 and the subiculum process sensory and motor cues to form a cognitive map encoding spatial, contextual, and emotional information, which they transmit throughout the brain. Do these cells constitute a single class or are there multiple cell types with specialized functions? Using unbiased cluster analysis, we show that there are two morphologically and electrophysiologically distinct principal cell types that carry hippocampal output. We show further that these two cell types are inversely modulated by the synergistic action of glutamate and acetylcholine acting on metabotropic receptors that are central to hippocampal function. Combined with prior connectivity studies, our results support a model of hippocampal processing in which the two pyramidal cell types are predominantly segregated into two parallel pathways that process distinct modalities of information.

Importance sampling for polarization-mode dispersion

We describe the application of importance sampling to Monte-Carlo simulations of polarization-mode dispersion (PMD) in optical fibers. The method allows rare differential group delay (DGD) events to be simulated much more efficiently than with standard Monte-Carlo methods and, thus, it can be used to assess PMD-induced system outage probabilities at realistic bit-error rates. We demonstrate the technique by accurately calculating the tails of the DGD probability distribution with a relatively small number of Monte-Carlo trials.

A synaptic mechanism for retinal adaptation to luminance and contrast.

The gain of signaling in primary sensory circuits is matched to the stimulus intensity by the process of adaptation. Retinal neural circuits adapt to visual scene statistics, including the mean (background adaptation) and the temporal variance (contrast adaptation) of the light stimulus. The intrinsic properties of retinal bipolar cells and synapses contribute to background and contrast adaptation, but it is unclear whether both forms of adaptation depend on the same cellular mechanisms. Studies of bipolar cell synapses identified synaptic mechanisms of gain control, but the relevance of these mechanisms to visual processing is uncertain because of the historical focus on fast, phasic transmission rather than the tonic transmission evoked by ambient light. Here, we studied use-dependent regulation of bipolar cell synaptic transmission evoked by small, ongoing modulations of membrane potential (VM) in the physiological range. We made paired whole-cell recordings from rod bipolar (RB) and AII amacrine cells in a mouse retinal slice preparation. Quasi-white noise voltage commands modulated RB VM and evoked EPSCs in the AII. We mimicked changes in background luminance or contrast, respectively, by depolarizing the VM or increasing its variance. A linear systems analysis of synaptic transmission showed that increasing either the mean or the variance of the presynaptic VM reduced gain. Further electrophysiological and computational analyses demonstrated that adaptation to mean potential resulted from both Ca channel inactivation and vesicle depletion, whereas adaptation to variance resulted from vesicle depletion alone. Thus, background and contrast adaptation apparently depend in part on a common synaptic mechanism.

Histone Methyltransferase MMSET/NSD2 Alters EZH2 Binding and Reprograms the Myeloma Epigenome through Global and Focal Changes in H3K36 and H3K27 Methylation

Overexpression of the histone methyltransferase MMSET in t(4;14)+ multiple myeloma patients is believed to be the driving factor in the pathogenesis of this subtype of myeloma. MMSET catalyzes dimethylation of lysine 36 on histone H3 (H3K36me2), and its overexpression causes a global increase in H3K36me2, redistributing this mark in a broad, elevated level across the genome. Here, we demonstrate that an increased level of MMSET also induces a global reduction of lysine 27 trimethylation on histone H3 (H3K27me3). Despite the net decrease in H3K27 methylation, specific genomic loci exhibit enhanced recruitment of the EZH2 histone methyltransferase and become hypermethylated on this residue. These effects likely contribute to the myeloma phenotype since MMSET-overexpressing cells displayed increased sensitivity to EZH2 inhibition. Furthermore, we demonstrate that such MMSET-mediated epigenetic changes require a number of functional domains within the protein, including PHD domains that mediate MMSET recruitment to chromatin. In vivo, targeting of MMSET by an inducible shRNA reversed histone methylation changes and led to regression of established tumors in athymic mice. Together, our work elucidates previously unrecognized interplay between MMSET and EZH2 in myeloma oncogenesis and identifies domains to be considered when designing inhibitors of MMSET function.