Stimulus-dependent maximum entropy models of neural population codes

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

Salmonella Type III Effector AvrA Stabilizes Cell Tight Junctions to Inhibit Inflammation in Intestinal Epithelial Cells

Salmonella Typhimurium is a major cause of human gastroenteritis. The Salmonella type III secretory system secretes virulence proteins, called effectors. Effectors are responsible for the alteration of tight junction (TJ) structure and function in intestinal epithelial cells. AvrA is a newly described bacterial effector found in Salmonella. We report here that AvrA expression stabilizes cell permeability and tight junctions in intestinal epithelial cells. Cells colonized with an AvrA-deficient bacterial strain (AvrA−) displayed decreased cell permeability, disruption of TJs, and an increased inflammatory response. Western blot data showed that TJ proteins, such as ZO-1, claudin-1, decreased after AvrA- colonization for only 1 hour. In contrast, cells colonized with AvrA-sufficient bacteria maintained cell permeability with stabilized TJ structure. This difference was confirmed in vivo. Fluorescent tracer studies showed increased fluorescence in the blood of mice infected with AvrA- compared to those infected with the AvrA-sufficient strains. AvrA- disrupted TJ structure and function and increased inflammation in vivo, compared to the AvrA- sufficient strain. Additionally, AvrA overexpression increased TJ protein expression when transfected into colonic epithelial cells. An intriguing aspect of this study is that AvrA stabilized TJs, even though the other TTSS proteins, SopB, SopE, and SopE2, are known to disrupt TJs. AvrA may play a role in stabilizing TJs and balancing the opposing action of other bacterial effectors. Our findings indicate an important role for the bacterial effector AvrA in regulation of intestinal epithelial cell TJs during inflammation. The role of AvrA represents a highly refined bacterial strategy that helps the bacteria survive in the host and dampen the inflammatory response

Gene expression during normal and FSHD myogenesis

<p>Abstract</p> <p>Background</p> <p>Facioscapulohumeral muscular dystrophy (FSHD) is a dominant disease linked to contraction of an array of tandem 3.3-kb repeats (D4Z4) at 4q35. Within each repeat unit is a gene, <it>DUX4</it>, that can encode a protein containing two homeodomains. A <it>DUX4 </it>transcript derived from the last repeat unit in a contracted array is associated with pathogenesis but it is unclear how.</p> <p>Methods</p> <p>Using exon-based microarrays, the expression profiles of myogenic precursor cells were determined. Both undifferentiated myoblasts and myoblasts differentiated to myotubes derived from FSHD patients and controls were studied after immunocytochemical verification of the quality of the cultures. To further our understanding of FSHD and normal myogenesis, the expression profiles obtained were compared to those of 19 non-muscle cell types analyzed by identical methods.</p> <p>Results</p> <p>Many of the ~17,000 examined genes were differentially expressed (> 2-fold, <it>p </it>< 0.01) in control myoblasts or myotubes vs. non-muscle cells (2185 and 3006, respectively) or in FSHD vs. control myoblasts or myotubes (295 and 797, respectively). Surprisingly, despite the morphologically normal differentiation of FSHD myoblasts to myotubes, most of the disease-related dysregulation was seen as dampening of normal myogenesis-specific expression changes, including in genes for muscle structure, mitochondrial function, stress responses, and signal transduction. Other classes of genes, including those encoding extracellular matrix or pro-inflammatory proteins, were upregulated in FSHD myogenic cells independent of an inverse myogenesis association. Importantly, the disease-linked <it>DUX4 </it>RNA isoform was detected by RT-PCR in FSHD myoblast and myotube preparations only at extremely low levels. Unique insights into myogenesis-specific gene expression were also obtained. For example, all four Argonaute genes involved in RNA-silencing were significantly upregulated during normal (but not FSHD) myogenesis relative to non-muscle cell types.</p> <p>Conclusions</p> <p><it>DUX4</it>'s pathogenic effect in FSHD may occur transiently at or before the stage of myoblast formation to establish a cascade of gene dysregulation. This contrasts with the current emphasis on toxic effects of experimentally upregulated <it>DUX4 </it>expression at the myoblast or myotube stages. Our model could explain why <it>DUX4</it>'s inappropriate expression was barely detectable in myoblasts and myotubes but nonetheless linked to FSHD.</p

Study of FoxA Pioneer Factor at Silent Genes Reveals Rfx-Repressed Enhancer at Cdx2 and a Potential Indicator of Esophageal Adenocarcinoma Development

Understanding how silent genes can be competent for activation provides insight into development as well as cellular reprogramming and pathogenesis. We performed genomic location analysis of the pioneer transcription factor FoxA in the adult mouse liver and found that about one-third of the FoxA bound sites are near silent genes, including genes without detectable RNA polymerase II. Virtually all of the FoxA-bound silent sites are within conserved sequences, suggesting possible function. Such sites are enriched in motifs for transcriptional repressors, including for Rfx1 and type II nuclear hormone receptors. We found one such target site at a cryptic “shadow” enhancer 7 kilobases (kb) downstream of the Cdx2 gene, where Rfx1 restricts transcriptional activation by FoxA. The Cdx2 shadow enhancer exhibits a subset of regulatory properties of the upstream Cdx2 promoter region. While Cdx2 is ectopically induced in the early metaplastic condition of Barrett's esophagus, its expression is not necessarily present in progressive Barrett's with dysplasia or adenocarcinoma. By contrast, we find that Rfx1 expression in the esophageal epithelium becomes gradually extinguished during progression to cancer, i.e, expression of Rfx1 decreased markedly in dysplasia and adenocarcinoma. We propose that this decreased expression of Rfx1 could be an indicator of progression from Barrett's esophagus to adenocarcinoma and that similar analyses of other transcription factors bound to silent genes can reveal unanticipated regulatory insights into oncogenic progression and cellular reprogramming

Spike-Based Bayesian-Hebbian Learning of Temporal Sequences

Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model's feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx). We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison