Search · four archives
Search · four archives
20 papers · ranked by Valyu relevance
João F. Guassi Moreira, Jennifer A. Silvers
The current prevailing approaches to analyzing task fMRI data in developmental cognitive neuroscience are brain connectivity and mass univariate task-based analyses, used either in isolation or as part of a broader analytic framework (e.g., BWAS). While these are powerful tools, it is somewhat surprising that…
Karen F. LaRocque, Tyler H. Davis, Jeanette A. Mumford, Russell A. Poldrack + 1 more
Pattern similarity analysis, which uses correlation to examine similarities between neural activation patterns evoked by different trials or conditions, are often leveraged to test hypotheses not easily answerable with univariate comparisons, such as how events are represented or processed and the relationships between…
Aurora Rizza, Tiziana Pedale, Serena Mastroberardino, Marta Olivetti Belardinelli + 4 more
The frontoparietal attention network plays a pivotal role during working memory (WM) maintenance, especially under high-load conditions. Nevertheless, there is ongoing debate regarding whether this network relies on supramodal or modality-specific neural signatures. In this study, we used multi-voxel pattern analysis…
Yusuke Sonobe, Toyoki Yamagata, Huixiang Yang, Yusuke Haruki + 1 more
The sense of body ownership, defined as the sensation that one’s body belongs to oneself, is a fundamental component of bodily self-consciousness. Several studies have shown the importance of multisensory integration for the emergence of the sense of body ownership, together with the involvement of the parieto-premotor…
Yanqing Wang, Xuerui Peng, Xueping Hu, Yongcong Shao
Choices between smaller certain reward and larger riskier reward are referred to as risky decision making. Numerous functional magnetic resonance imaging (fMRI) studies have investigated the neural substrates of risky decision making via conventional univariate analytical approaches, revealing dissociable activation of…
Xuelei Wang, Jana Zweerings, Michael Lührs, Fengyu Cong + 5 more
Identifying informative voxels is a critical, yet challenging step in functional magnetic resonance imaging (fMRI), particularly for multivariate analyses involving multiple related conditions. Existing approaches often rely on predefined regions of interest (ROIs) or activation-based criteria, which may be…
Qiang Li, Dinghong Gong, Jie Shen, Chang Rao + 2 more
Compared with traditional volume space-based multivariate pattern analysis (MVPA), surface space-based MVPA has many advantages and has received increasing attention. However, surface space-based MVPA requires considerable programming and is therefore difficult for people without a programming foundation. To address…
Pedro A. Luque Laguna, Ahmad Beyh, Francisco de S. Requejo, Richard Stones + 5 more
Most neuroimaging modalities use regular grids of voxels to represent the three-dimensional space occupied by the brain. However, a regular 3D voxel grid does not reflect the anatomical and topological complexity represented by the brain’s white matter connections. In contrast, tractography reconstructions based on…
Joram Soch
In multivariate pattern analysis (MVPA) for functional magnetic resonance imaging (fMRI) signals, trial-wise response amplitudes are sometimes estimated using a general linear model (GLM) with one onset regressor for each trial. When using rapid event-related designs with trials closely spaced in time, those estimates…
Xiangyang He, Yubo Tao, Shuoliu Yang, Haoran Dai + 1 more
—Relationships in scientific data, such as the numerical and spatial distribution relations of features in univariate data, the scalar-value combinations' relations in multivariate data, and the association of volumes in time-varying and ensemble data, are intricate and complex. This paper presents voxel2vec, a novel…
Naimul Khan, Riadh Ksantini, Ling Guan
Transfer Function (TF) generation is a fundamental problem in Direct Volume Rendering (DVR). A TF maps voxels to color and opacity values to reveal inner structures. Existing TF tools are complex and unintuitive for the users who are more likely to be medical professionals than computer scientists. In this paper, we…
Jiyang Jiang, Dadong Wang, Yang Song, Perminder S. Sachdev + 1 more
- 1. Centre for Healthy Brain Ageing, Discipline of Psychiatry and Mental Health, School of Clinical Medicine, Faculty of Medicine, University of New South Wales, NSW 2052, Australia. - 2. Quantitative Imaging Research Team, Data61, CSIRO, Marsfield, NSW 2122, Australia. - 3. School of Computer Science and Engineering…
Elaheh Hatamimajoumerd, Alireza Talebpour
Undoubtedly, textural property of an image is one of the most important features in object recognition task in both human and computer vision applications. Here, we investigated the neural signatures of four well-known statistical texture features including contrast, homogeneity, energy, and correlation computed from…
Zhengyuan Zhang, Ping Chen, Yajun Liu, Yi He + 1 more
Multi-visual pattern mining plays an important role in image classification, retrieval, and other fields. A multi visual pattern mining algorithm based on variational inference Gaussian mixture model and pattern activation response graph is introduced to address the issues of insufficient frequency and discriminability…
Liang Zhou, Xinyi Gou, Daniel A. Weiskopf
We introduce continuous indexed points for improved multivariate volume visualization. Indexed points represent linear structures in parallel coordinates and can be used to encode local correlation of multivariate (including multifield, multifaceted, and multiattribute) volume data. First, we perform local linear…
Ajay D. Halai, Richard N. Henson, Paola Finoia, Marta M. Correia
The Blood Oxygenation Level Dependent (BOLD) signal, as measured using functional magnetic resonance imaging (fMRI), is known to vary in sensitivity across the brain due to magnetic susceptibility artefacts. In particular, the ventral anterior temporal lobes (vATL) have been implicated with semantic cognition using…
Atif Shah, Maged S. Al-Shaibani, Moataz Ahmad, Reem F. Bunyan
Methodology: In this study, we review the different approaches that have been used in computer-aided detection and segmentation of MS lesions. Our review resulted in categorizing MS lesion segmentation approaches into six broad categories: data-driven, statistical, supervised machine learning, unsupervised machine…
Matheus Müller Pereira da Silva, Isabella Alvim Guedes, Fábio Lima Custódio, Laurent Emmanuel Dardenne
A critical aspect of successful deep learning (DL) modelling in computer-aided drug discovery (CADD) is the representation of biomolecular data. Voxel grid representations have emerged as a straightforward method for depicting 3D molecular structures of protein-ligand complexes. Proper structural preparation of these…
Ajay D. Halai, Richard N. Henson, Paola Finoia, Marta M. Correia
The blood oxygenation level dependent (BOLD) signal, as measured using functional magnetic resonance imaging (fMRI), is known to vary in sensitivity across the brain due to magnetic susceptibility artefacts. For example, the ventral anterior temporal lobes have been implicated with semantic cognition using convergent…
Alexandre Benatti, Luciano da Fontoura Costa
The coincidence similarity index, based on a combination of the Jaccard and overlap similarity indices, has noticeable properties in comparing and classifying data, including enhanced selectivity and sensitivity, intrinsic normalization, and robustness to data perturbations and outliers. These features allow multiset…