2,079 research outputs found
Efficient coding of natural images in the mouse visual cortex.
How the activity of neurons gives rise to natural vision remains a matter of intense investigation. The mid-level visual areas along the ventral stream are selective to a common class of natural images-textures-but a circuit-level understanding of this selectivity and its link to perception remains unclear. We addressed these questions in mice, first showing that they can perceptually discriminate between textures and statistically simpler spectrally matched stimuli, and between texture types. Then, at the neural level, we found that the secondary visual area (LM) exhibited a higher degree of selectivity for textures compared to the primary visual area (V1). Furthermore, textures were represented in distinct neural activity subspaces whose relative distances were found to correlate with the statistical similarity of the images and the mice's ability to discriminate between them. Notably, these dependencies were more pronounced in LM, where the texture-related subspaces were smaller than in V1, resulting in superior stimulus decoding capabilities. Together, our results demonstrate texture vision in mice, finding a linking framework between stimulus statistics, neural representations, and perceptual sensitivity-a distinct hallmark of efficient coding computations
Intra-varietal variability of Romanesco variety (Vitis vinifera L.)
Most historical sources that describe the presence of Romanesco variety in vine-growing
areas of Lazio Region (Italy) highlighted the variability of morphological traits within the variety.
This partly justifies the presence of different synonyms, true or presumed, reported by many authors
for this grape variety. With the aim of analysing this variability, eight accessions related to the
variety, collected in Lazio Region and grown in the DAFNE grape germplasm collection, have been
characterized over five productive seasons. The ampelographic description was carried out using 50
OIV morphological descriptors and ampelometric analyses were carried out on mature leaves by
SuperAmpelo software. The DNA of the different accessions, extracted from young leaves, was
analyzed using 14 microsatellite loci. Furthermore, at harvest, the grapes of each accession were
sampled to assess main compositive characteristics. Results showed differences among accessions
on some ampelographic descriptors of the mature leaf, of the bunch, and on phenological stages.
Microsatellite profiles allowed for classification of the accessions into three distinct groups.
Qualitative analysis of the berry skin showed differences among accessions in the content of the
main classes of phenolic compounds
COVID 19: a clue from innate immunity
The recent COVID-19 pandemic has had a significant impact on our lives and has rapidly expanded to reach more than 4 million cases worldwide by May 2020. These cases are characterized by extreme variability, from a mild or asymptomatic form lasting for a few days up to severe forms of interstitial pneumonia that may require ventilatory therapy and can lead to patient death. Several hypotheses have been drawn up to understand the role of the interaction between the infectious agent and the immune system in the development of the disease and the most severe forms; the role of the cytokine storm seems important. Innate immunity, as one of the first elements of guest interaction with different infectious agents, could play an important role in the development of the cytokine storm and be responsible for boosting more severe forms. Therefore, it seems important to study also this important arm of the immune system to adequately understand the pathogenesis of the disease. Research on this topic is also needed to develop therapeutic strategies for treatment of this disease
Learning intrinsic excitability in medium spiny neurons
We present an unsupervised, local activation-dependent learning rule for
intrinsic plasticity (IP) which affects the composition of ion channel
conductances for single neurons in a use-dependent way. We use a
single-compartment conductance-based model for medium spiny striatal neurons in
order to show the effects of parametrization of individual ion channels on the
neuronal activation function. We show that parameter changes within the
physiological ranges are sufficient to create an ensemble of neurons with
significantly different activation functions. We emphasize that the effects of
intrinsic neuronal variability on spiking behavior require a distributed mode
of synaptic input and can be eliminated by strongly correlated input. We show
how variability and adaptivity in ion channel conductances can be utilized to
store patterns without an additional contribution by synaptic plasticity (SP).
The adaptation of the spike response may result in either "positive" or
"negative" pattern learning. However, read-out of stored information depends on
a distributed pattern of synaptic activity to let intrinsic variability
determine spike response. We briefly discuss the implications of this
conditional memory on learning and addiction.Comment: 20 pages, 8 figure
Infections and Biological Therapy in Patients with Rheumatic Diseases
Long-term extension studies and observational drug registers have revealed an increased risk of serious infections in patients treated with anti-tumor necrosis factor agents, particularly infliximab, etanercept and adalimumab. The same may be true for the newer biological drugs rituximab, tocilizumab and abatacept, although this has yet to be confirmed by long-term observational studies. We review the risk of tuberculosis, herpes zoster and other opportunistic infections, and the recommendations for screening for tuberculosis and hepatitis B and C infections in patients with rheumatoid arthritis, with the aim of informing patients and encouraging greater awareness among physicians
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Measurement of masses in the [Formula: see text] system by kinematic endpoints in pp collisions at [Formula: see text].
A simultaneous measurement of the top-quark, W-boson, and neutrino masses is reported for [Formula: see text] events selected in the dilepton final state from a data sample corresponding to an integrated luminosity of 5.0 fb-1 collected by the CMS experiment in pp collisions at [Formula: see text]. The analysis is based on endpoint determinations in kinematic distributions. When the neutrino and W-boson masses are constrained to their world-average values, a top-quark mass value of [Formula: see text] is obtained. When such constraints are not used, the three particle masses are obtained in a simultaneous fit. In this unconstrained mode the study serves as a test of mass determination methods that may be used in beyond standard model physics scenarios where several masses in a decay chain may be unknown and undetected particles lead to underconstrained kinematics
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Performance of photon reconstruction and identification with the CMS detector in proton-proton collisions at √s = 8 TeV
A description is provided of the performance of the CMS detector for photon reconstruction and identification in proton-proton collisions at a centre-of-mass energy of 8 TeV at the CERN LHC. Details are given on the reconstruction of photons from energy deposits in the electromagnetic calorimeter (ECAL) and the extraction of photon energy estimates. The reconstruction of electron tracks from photons that convert to electrons in the CMS tracker is also described, as is the optimization of the photon energy reconstruction and its accurate modelling in simulation, in the analysis of the Higgs boson decay into two photons. In the barrel section of the ECAL, an energy resolution of about 1% is achieved for unconverted or late-converting photons from Hγγ decays. Different photon identification methods are discussed and their corresponding selection efficiencies in data are compared with those found in simulated events
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