Zero-shot Learning of Individualized Task Contrast Prediction from Resting-state Functional Connectomes

Given sufficient pairs of resting-state and task-evoked fMRI scans from subjects, it is possible to train ML models to predict subject-specific task-evoked activity using resting-state functional MRI (rsfMRI) scans. However, while rsfMRI scans are relatively easy to collect, obtaining sufficient task fMRI scans is much harder as it involves more complex experimental designs and procedures. Thus, the reliance on scarce paired data limits the application of current techniques to only tasks seen during training. We show that this reliance can be reduced by leveraging group-average contrasts, enabling zero-shot predictions for novel tasks. Our approach, named OPIC (short for Omni-Task Prediction of Individual Contrasts), takes as input a subject's rsfMRI-derived connectome and a group-average contrast, to produce a prediction of the subject-specific contrast. Similar to zero-shot learning in large language models using special inputs to obtain answers for novel natural language processing tasks, inputting group-average contrasts guides the OPIC model to generalize to novel tasks unseen in training. Experimental results show that OPIC's predictions for novel tasks are not only better than simple group-averages, but are also competitive with a state-of-the-art model's in-domain predictions that was trained using in-domain tasks' data.Comment: Accepted at DALI@MICCAI 202

Universal optical amplification without nonlinearity

We propose and experimentally realize a new scheme for universal phase-insensitive optical amplification. The presented scheme relies only on linear optics and homodyne detection, thus circumventing the need for nonlinear interaction between a pump field and the signal field. The amplifier demonstrates near optimal quantum noise limited performance for a wide range of amplification factors.Comment: 5 pages, 4 figure

Out-of-plane dynamic stability analysis of curved beams subjected to uniformly distributed radial loading

The out-of-plane stability of tapered cross-sectioned thin curved beams under uniformly distributed radial loading is investigated by using the Finite Element Method. Solutions referred to as Bolotin’s approach are investigated for the dynamic stability analysis and the first unstable regions are examined. Out-of-plane vibrations and out-plane buckling analyses are also considered. In addition, the results obtained in this study are compared with the results of other investigators in existing literature for the fundamental frequency and critical lateral buckling load. The effects of subtended angle, variations of cross-section and dynamic load parameter on the stability regions are shown in graphics.За допомогою методу скінчених елементів проаналізовано бокову стійкість викривленої звуженої у кінці тонкої балки при однорідно розподіленому радіальному навантаженні.Розв‘язки у вигляді наближення Болотіна досліджені в рамках аналізу динамічної стійкості. Також вивчені бокові коливання і бокове випучення балки. Отримані результати щодо основної частоти та критичного навантаження при боковому випученні порівняні з іншими опублікованими результатами. На рисунках показано вплив утвореного дугою кута зміни поперечного перерізу та параметру динамічного навантаження на область стійкості

Experimental Demonstration of Squeezed State Quantum Averaging

We propose and experimentally demonstrate a universal quantum averaging process implementing the harmonic mean of quadrature variances. The harmonic mean protocol can be used to efficiently stabilize a set of fragile squeezed light sources with statistically fluctuating noise levels. The averaged variances are prepared probabilistically by means of linear optical interference and measurement induced conditioning. We verify that the implemented harmonic mean outperforms the standard arithmetic mean strategy. The effect of quantum averaging is experimentally tested both for uncorrelated and partially correlated noise sources with sub-Poissonian shot noise or super-Poissonian shot noise characteristics.Comment: 4 pages, 5 figure

Predicting Activation Across Individuals with Resting-State Functional Connectivity Based Multi-Atlas Label Fusion

The alignment of brain imaging data for functional neuroimaging studies is challenging due to the discrepancy between correspondence of morphology, and equivalence of functional role. In this paper we map functional activation areas across individuals by a multi-atlas label fusion algorithm in a functional space. We learn the manifold of resting-state fMRI signals in each individual, and perform manifold alignment in an embedding space. We then transfer activation predictions from a source population to a target subject via multi-atlas label fusion. The cost function is derived from the aligned manifolds, so that the resulting correspondences are derived based on the similarity of intrinsic connectivity architecture. Experiments show that the resulting label fusion predicts activation evoked by various experiment conditions with higher accuracy than relying on morphological alignment. Interestingly, the distribution of this gain is distributed heterogeneously across the cortex, and across tasks. This offers insights into the relationship between intrinsic connectivity, morphology and task activation. Practically, the mechanism can serve as prior, and provides an avenue to infer task-related activation in individuals for whom only resting data is available. Keywords: Functional Connectivity, Cortical Surface, Task Activation, Target Subject, Intrinsic ConnectivityCongressionally Directed Medical Research Programs (U.S.) (Grant PT100120)Eunice Kennedy Shriver National Institute of Child Health and Human Development (U.S.) (R01HD067312)Neuroimaging Analysis Center (U.S.) (P41EB015902)Oesterreichische Nationalbank (14812)Oesterreichische Nationalbank (15929)Seventh Framework Programme (European Commission) (FP7 2012-PIEF-GA-33003

Multidimensional heritability analysis of neuroanatomical shape

In the dawning era of large-scale biomedical data, multidimensional phenotype vectors will play an increasing role in examining the genetic underpinnings of brain features, behaviour and disease. For example, shape measurements derived from brain MRI scans are multidimensional geometric descriptions of brain structure and provide an alternate class of phenotypes that remains largely unexplored in genetic studies. Here we extend the concept of heritability to multidimensional traits, and present the first comprehensive analysis of the heritability of neuroanatomical shape measurements across an ensemble of brain structures based on genome-wide SNP and MRI data from 1,320 unrelated, young and healthy individuals. We replicate our findings in an extended twin sample from the Human Connectome Project (HCP). Our results demonstrate that neuroanatomical shape can be significantly heritable, above and beyond volume, and can serve as a complementary phenotype to study the genetic determinants and clinical relevance of brain structure.National Institute for Biomedical Imaging and Bioengineering (U.S.) (P41EB015896)United States. National Institutes of Health (S10RR023043)United States. National Institutes of Health (S10RR023401)United States. National Institutes of Health (K25CA181632)United States. National Institutes of Health (K01MH099232)United States. National Institutes of Health (K99MH101367)United States. National Institutes of Health (R21AG050122-01A1)United States. National Institutes of Health (R41AG052246-01)United States. National Institutes of Health (1K25EB013649-01)United States. National Institutes of Health (K24MH094614)United States. National Institutes of Health (R01MH101486

Distributed phase-covariant cloning with atomic ensembles via quantum Zeno dynamics

We propose an interesting scheme for distributed orbital state quantum cloning with atomic ensembles based on the quantum Zeno dynamics. These atomic ensembles which consist of identical three-level atoms are trapped in distant cavities connected by a single-mode integrated optical star coupler. These qubits can be manipulated through appropriate modulation of the coupling constants between atomic ensemble and classical field, and the cavity decay can be largely suppressed as the number of atoms in the ensemble qubits increases. The fidelity of each cloned qubit can be obtained with analytic result. The present scheme provides a new way to construct the quantum communication network.Comment: 5 pages, 4 figure