Acoustic cues to visual detection: a classification image study.

A non-informative sound is known to improve contrast detection thresholds for a synchronous visual target (M. Lippert, N. K. Logothetis, & C. Kayser, 2007). We investigated the spatio-temporal characteristics of the mechanisms underlying this crossmodal effect by using a classification image paradigm specifically suited to investigate perceptual templates across both space and time (P. Neri & D. J. Heeger, 2002). A bright bar was embedded in 2D (space-time) dynamic noise and observers were asked to detect its presence in both unimodal (only visual) and bimodal (audio-visual) conditions. Classification image analysis was performed and the 1st and 2nd order kernels were derived. Our results show that the cross-modal facilitation of detection consists in a reduction of activity of the early mechanisms elicited by the onset of the stimulation and not directly involved in the identification of the target. In fact, the sound sharpens the 2nd order kernels (involved in target detection) by suppressing the activation preceding the target, whereas it does not influence the 1st order kernels. These data suggest that the sound affects some non-linear process involved with the detection of a visual stimulus by, decreasing the activity of contrast energy filters temporally uncorrelated with the target, hence reducing temporal uncertainty

NAVIGATOR: an Italian regional imaging biobank to promote precision medicine for oncologic patients.

NAVIGATOR is an Italian regional project boosting precision medicine in oncology with the aim of making it more predictive, preventive, and personalised by advancing translational research based on quantitative imaging and integrative omics analyses. The project's goal is to develop an open imaging biobank for the collection and preservation of a large amount of standardised imaging multimodal datasets, including computed tomography, magnetic resonance imaging, and positron emission tomography data, together with the corresponding patient-related and omics-related relevant information extracted from regional healthcare services using an adapted privacy-preserving model. The project is based on an open-source imaging biobank and an open-science oriented virtual research environment (VRE). Available integrative omics and multi-imaging data of three use cases (prostate cancer, rectal cancer, and gastric cancer) will be collected. All data confined in NAVIGATOR (i.e., standard and novel imaging biomarkers, non-imaging data, health agency data) will be used to create a digital patient model, to support the reliable prediction of the disease phenotype and risk stratification. The VRE that relies on a well-established infrastructure, called D4Science.org, will further provide a multiset infrastructure for processing the integrative omics data, extracting specific radiomic signatures, and for identification and testing of novel imaging biomarkers through big data analytics and artificial intelligence