129 research outputs found

    Search for the standard model Higgs boson at LEP

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    Anodal Transcranial Direct Current Stimulation Reduces Psychophysically Measured Surround Suppression in the Human Visual Cortex

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    Transcranial direct current stimulation (tDCS) is a safe, non-invasive technique for transiently modulating the balance of excitation and inhibition within the human brain. It has been reported that anodal tDCS can reduce both GABA mediated inhibition and GABA concentration within the human motor cortex. As GABA mediated inhibition is thought to be a key modulator of plasticity within the adult brain, these findings have broad implications for the future use of tDCS. It is important, therefore, to establish whether tDCS can exert similar effects within non-motor brain areas. The aim of this study was to assess whether anodal tDCS could reduce inhibitory interactions within the human visual cortex. Psychophysical measures of surround suppression were used as an index of inhibition within V1. Overlay suppression, which is thought to originate within the lateral geniculate nucleus (LGN), was also measured as a control. Anodal stimulation of the occipital poles significantly reduced psychophysical surround suppression, but had no effect on overlay suppression. This effect was specific to anodal stimulation as cathodal stimulation had no effect on either measure. These psychophysical results provide the first evidence for tDCS-induced reductions of intracortical inhibition within the human visual cortex

    The Time Course of Segmentation and Cue-Selectivity in the Human Visual Cortex

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    Texture discontinuities are a fundamental cue by which the visual system segments objects from their background. The neural mechanisms supporting texture-based segmentation are therefore critical to visual perception and cognition. In the present experiment we employ an EEG source-imaging approach in order to study the time course of texture-based segmentation in the human brain. Visual Evoked Potentials were recorded to four types of stimuli in which periodic temporal modulation of a central 3° figure region could either support figure-ground segmentation, or have identical local texture modulations but not produce changes in global image segmentation. The image discontinuities were defined either by orientation or phase differences across image regions. Evoked responses to these four stimuli were analyzed both at the scalp and on the cortical surface in retinotopic and functional regions-of-interest (ROIs) defined separately using fMRI on a subject-by-subject basis. Texture segmentation (tsVEP: segmenting versus non-segmenting) and cue-specific (csVEP: orientation versus phase) responses exhibited distinctive patterns of activity. Alternations between uniform and segmented images produced highly asymmetric responses that were larger after transitions from the uniform to the segmented state. Texture modulations that signaled the appearance of a figure evoked a pattern of increased activity starting at ∌143 ms that was larger in V1 and LOC ROIs, relative to identical modulations that didn't signal figure-ground segmentation. This segmentation-related activity occurred after an initial response phase that did not depend on the global segmentation structure of the image. The two cue types evoked similar tsVEPs up to 230 ms when they differed in the V4 and LOC ROIs. The evolution of the response proceeded largely in the feed-forward direction, with only weak evidence for feedback-related activity

    Context Matters: The Illusive Simplicity of Macaque V1 Receptive Fields

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    Even in V1, where neurons have well characterized classical receptive fields (CRFs), it has been difficult to deduce which features of natural scenes stimuli they actually respond to. Forward models based upon CRF stimuli have had limited success in predicting the response of V1 neurons to natural scenes. As natural scenes exhibit complex spatial and temporal correlations, this could be due to surround effects that modulate the sensitivity of the CRF. Here, instead of attempting a forward model, we quantify the importance of the natural scenes surround for awake macaque monkeys by modeling it non-parametrically. We also quantify the influence of two forms of trial to trial variability. The first is related to the neuron’s own spike history. The second is related to ongoing mean field population activity reflected by the local field potential (LFP). We find that the surround produces strong temporal modulations in the firing rate that can be both suppressive and facilitative. Further, the LFP is found to induce a precise timing in spikes, which tend to be temporally localized on sharp LFP transients in the gamma frequency range. Using the pseudo R[superscript 2] as a measure of model fit, we find that during natural scene viewing the CRF dominates, accounting for 60% of the fit, but that taken collectively the surround, spike history and LFP are almost as important, accounting for 40%. However, overall only a small proportion of V1 spiking statistics could be explained (R[superscript 2]~5%), even when the full stimulus, spike history and LFP were taken into account. This suggests that under natural scene conditions, the dominant influence on V1 neurons is not the stimulus, nor the mean field dynamics of the LFP, but the complex, incoherent dynamics of the network in which neurons are embedded.National Institutes of Health (U.S.) (K25 NS052422-02)National Institutes of Health (U.S.) (DP1 ODOO3646

    Search for Higgs Boson Pair Production in the Four b Quark Final State in Proton-Proton Collisions at root s=13 TeV

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    A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution

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    We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton-proton collisions at an energy of s = 13 TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 fb - 1 . A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to b b ÂŻ

    Search for invisible decays of the Higgs boson produced via vector boson fusion in proton-proton collisions at root s=13 TeV

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    Observation of triple J/ψ meson production in proton-proton collisions

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    Data availability: Tabulated results are provided in the HEPData record for this analysis71. Release and preservation of data used by the CMS Collaboration as the basis for publications is guided by the CMS policy as stated in CMS data preservation, re-use and open access policy.Code availability: The CMS core software is publically available at https://github.com/cms-sw/cmssw.Copyright . Protons consist of three valence quarks, two up-quarks and one down-quark, held together by gluons and a sea of quark-antiquark pairs. Collectively, quarks and gluons are referred to as partons. In a proton-proton collision, typically only one parton of each proton undergoes a hard scattering – referred to as single-parton scattering – leaving the remainder of each proton only slightly disturbed. Here, we report the study of double- and triple-parton scatterings through the simultaneous production of three J/ψ mesons, which consist of a charm quark-antiquark pair, in proton-proton collisions recorded with the CMS experiment at the Large Hadron Collider. We observed this process – reconstructed through the decays of J/ψ mesons into pairs of oppositely charged muons – with a statistical significance above five standard deviations. We measured the inclusive fiducial cross-section to be 272+141−104(stat)±17(syst)fb, and compared it to theoretical expectations for triple-J/ψ meson production in single-, double- and triple-parton scattering scenarios. Assuming factorization of multiple hard-scattering probabilities in terms of single-parton scattering cross-sections, double- and triple-parton scattering are the dominant contributions for the measured process.SCOAP3.Change history: 27 February 2023A Correction to this paper has been published: https://doi.org/10.1038/s41567-023-01992-
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