34 research outputs found

    Stimulus-dependent maximum entropy models of neural population codes

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    Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. To be able to infer a model for this distribution from large-scale neural recordings, we introduce a stimulus-dependent maximum entropy (SDME) model---a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. The model is able to capture the single-cell response properties as well as the correlations in neural spiking due to shared stimulus and due to effective neuron-to-neuron connections. Here we show that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. As a result, the SDME model gives a more accurate account of single cell responses and in particular outperforms uncoupled models in reproducing the distributions of codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like surprise and information transmission in a neural population.Comment: 11 pages, 7 figure

    A Synaptic Mechanism for Temporal Filtering of Visual Signals

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    The visual system transmits information about fast and slow changes in light intensity through separate neural pathways. We used in vivo imaging to investigate how bipolar cells transmit these signals to the inner retina. We found that the volume of the synaptic terminal is an intrinsic property that contributes to different temporal filters. Individual cells transmit through multiple terminals varying in size, but smaller terminals generate faster and larger calcium transients to trigger vesicle release with higher initial gain, followed by more profound adaptation. Smaller terminals transmitted higher stimulus frequencies more effectively. Modeling global calcium dynamics triggering vesicle release indicated that variations in the volume of presynaptic compartments contribute directly to all these differences in response dynamics. These results indicate how one neuron can transmit different temporal components in the visual signal through synaptic terminals of varying geometries with different adaptational properties

    Synaptic and circuit mechanisms promoting broadband transmission of olfactory stimulus dynamics

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    Sensory stimuli fluctuate on many timescales. However, short-term plasticity causes synapses to act as temporal filters, limiting the range of frequencies they can transmit. How synapses in vivo might transmit a range of frequencies in spite of short-term plasticity is poorly understood. The first synapse in the Drosophila olfactory system exhibits short-term depression, and yet can transmit broadband signals. Here we describe two mechanisms that broaden the frequency characteristics of this synapse. First, two distinct excitatory postsynaptic currents transmit signals on different timescales. Second, presynaptic inhibition dynamically updates synaptic properties to promote accurate transmission of signals across a wide range of frequencies. Inhibition is transient but grows slowly, and simulations show that these two features of inhibition promote broadband synaptic transmission. Dynamic inhibition is often thought to restrict the temporal patterns that a neuron responds to, but our results illustrate a different idea: inhibition can expand the bandwidth of neural coding

    Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the Retina

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    When visual contrast changes, retinal ganglion cells adapt by adjusting their sensitivity as well as their temporal filtering characteristics. The latter has classically been described by contrast-induced gain changes that depend on temporal frequency. Here, we explored a new perspective on contrast-induced changes in temporal filtering by using spike-triggered covariance analysis to extract multiple parallel temporal filters for individual ganglion cells. Based on multielectrode-array recordings from ganglion cells in the isolated salamander retina, we found that contrast adaptation of temporal filtering can largely be captured by contrast-invariant sets of filters with contrast-dependent weights. Moreover, differences among the ganglion cells in the filter sets and their contrast-dependent contributions allowed us to phenomenologically distinguish three types of filter changes. The first type is characterized by newly emerging features at higher contrast, which can be reproduced by computational models that contain response-triggered gain-control mechanisms. The second type follows from stronger adaptation in the Off pathway as compared to the On pathway in On-Off-type ganglion cells. Finally, we found that, in a subset of neurons, contrast-induced filter changes are governed by particularly strong spike-timing dynamics, in particular by pronounced stimulus-dependent latency shifts that can be observed in these cells. Together, our results show that the contrast dependence of temporal filtering in retinal ganglion cells has a multifaceted phenomenology and that a multi-filter analysis can provide a useful basis for capturing the underlying signal-processing dynamics

    Epstein-Barr Virus Latent Membrane Protein 2 Effects on Epithelial Acinus Development Reveal Distinct Requirements for the PY and YEEA motifs

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    Epstein-Barr virus (EBV) is a gammaherpesvirus associated with numerous cancers, including the epithelial cancers nasopharyngeal carcinoma (NPC) and gastric carcinoma. The latent membrane protein 2 (LMP2) encoded by EBV is consistently detected in NPC tumors and promotes a malignant phenotype when expressed in epithelial cells by inducing transformation and migration and inhibiting differentiation. Grown in three dimensions (3D) on Matrigel, the nontumorigenic mammary epithelial cell line MCF10A forms hollow, spherical acinar structures that maintain normal glandular features. Expression of oncogenes in these cells allows for the study of multiple aspects of tumor development in a 3D culture system. This study sought to examine the effects of LMP2 on the generation of MCF10A acini. LMP2 expression induced abnormal acini that were large, misshapen, and filled, indicating that LMP2 induced proliferation, impaired cellular polarization, and induced resistance to cell death, leading to luminal filling. Induction of cell death resistance required the PY, immunoreceptor tyrosine activation motif (ITAM), and YEEA signaling domains of LMP2 and activation of the Src and Akt signaling pathways. The PY domain was required for the inhibition of anoikis and also the delayed proliferative arrest of the LMP2-expressing cells. In addition to directly altering acinus formation, expression of LMP2 also induced morphological and protein expression changes consistent with epithelial-mesenchymal transition (EMT) in a manner that required only the YEEA signaling motif of LMP2. These findings indicate that LMP2 has considerable transforming properties that are not evident in standard tissue culture and requires the ability of LMP2A to bind ubiquitin ligases and Src family kinases
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