21 papers · ranked by Valyu relevance
Nivedita Daimiwal, Mahalingam Sundhararajan, Revati Shriram
— Brain-mapping techniques have proven to be vital in understanding the molecular, cellular, and functional mechanisms of the brain. Normal anatomical imaging can provide structural information on certain abnormalities in the brain. However there are many neurological disorders for which only structure studies are not…
Julia Moser, Sanju Koirala, Thomas Madison, Alyssa K. Labonte + 13 more
The characterization of individual functional brain organization with Precision Functional Mapping has provided important insights in recent years in adults. However, little is known about the ontogeny of inter-individual differences in brain functional organization during human development, but precise…
Matthieu M. de Wit, Heath E. Matheson
Mainstream cognitive neuroscience aims to build mechanistic explanations of behavior by mapping abilities described at the organismal level via the subpersonal level of computation onto specific brain networks. We provide an integrative review of these commitments and their mismatch with empirical research findings.…
Daniele Mortari, David Anas
This work presents an initial analysis of using bijective mappings to extend the Theory of Functional Connections to non-rectangular two-dimensional domains. Specifically, this manuscript proposes three different mappings techniques: a) complex mapping, b) projection mapping, and c) polynomial mapping. In that respect…
Yaqian Yang, Shaoting Tang, Xin Wang, Yi Zhen + 4 more
'Hongwei Zheng' 'Longzhao Liu' 'Zhiming Zheng'] While brain function is supported and constrained by the underlying structure, the connectome-based link estimated by current approaches is either relatively moderate or accompanied by high model complexity, with the essential principles underlying structure-function…
Jules R. Dugré
Human brain mapping has traditionally relied on univariate approaches to characterize regional activity, whereas more recent work focuses on interactions between regions to capture network-level organization. Despite their parallel development, growing evidence suggests that integrating both approaches is critical for…
Ping Wang, Xinli Luo, Xi-Nian Zuo
The expanding scale and complexity of functional brain image datasets require space-time analytics. Spacetime concordance (STC) meets this need through an adaptive and robust framework optimized for high-speed analysis. At the core of STC, the Regional Functional Affinity (RFA) metric quantifies functional diversity…
David Papo
Standard neuroimaging techniques provide non-invasive access not only to human brain anatomy but also to its physiology. The activity recorded with these techniques is generally called functional imaging, but what is observed per se is an instance of dynamics, from which functional brain activity should be extracted.…
Joshua R. Williams, Ruoting Yang, John L. Clifford, Daniel Watson + 5 more
'Ross Campbell' 'Derese Getnet' 'Raina Kumar' 'Rasha Hammamieh' 'Marti Jett'] Background Life science research is moving quickly towards large-scale experimental designs that are comprised of multiple tissues, time points, and samples. Omic time-series experiments offer answers to three big questions: what collective…
Evan Collins, Omar Chishti, Sami Obaid, Hari McGrath + 7 more
'Xilin Shen' 'Jagriti Arora' 'Xenophon Papademetris' 'R. Todd Constable' 'Dennis D. Spencer' 'Hitten P. Zaveri'] Functional coactivation between human brain regions is partly explained by white matter connections; however, how the structure-function relationship varies by function remains unclear. Here, we reference…
Craig Poskanzer, Stefano Anzellotti
Here, we propose a novel technique to investigate nonlinear interactions between brain regions that captures both the strength and type of the functional relationship. Inspired by the field of functional analysis, we propose that the relationship between activity in separate brain areas can be viewed as a point in…
Authors not listed
Chemical functional group annotation provides a mechanistically meaningful framework to interpret model outcomes and guide synthetic strategies. Here, we present SMARTS-RX—a curated, hierarchical ontology of 406 SMARTS-based functional group descriptors—designed to characterize chemically relevant and reactive…
Veronica Diveica, Michael C. Riedel, Taylor Salo, Angela R. Laird + 2 more
The left inferior frontal gyrus (LIFG) has been ascribed key roles in numerous cognitive domains, including language, executive function and social cognition. However, its functional organisation, and how the specific areas implicated in these cognitive domains relate to each other, is unclear. Possibilities include…
Julio A. Peraza, Taylor Salo, Michael C. Riedel, Katherine L. Bottenhorn + 14 more
Macroscale gradients have emerged as a central principle for understanding functional brain organization. Previous studies have demonstrated that a principal gradient of connectivity in the human brain exists, with unimodal primary sensorimotor regions situated at one end, and transmodal regions associated with the…
Authors not listed
Curried functions provide a systematic way of transforming multi-argument functions into nested singleargument functions. This transformation allows partial application and supports many central principles of functional programming. Their extension, called curried 𝑘-ary functions, naturally generalizes the familiar…
Philipp Rosenthal, Niels Demke, Frank Mantwill, Oliver Niggemann
The presented approach defines the decomposition problem in terms of a planning problem—a well established field in Artificial Intelligence. For the planning problem, logic-based solvers can be used to find solutions that compute a useful function structure for the design process. Well-known function libraries from…
Jonathan Fine, Anand Rasjashekar, Krupal P. Jethava, Gaurav Chopra
State-of-the-art identification of the functional groups present in an unknown chemical entity requires expertise of a skilled spectroscopist to analyse and interpret Fourier Transform Infra-Red (FTIR), Mass Spectroscopy (MS) and/or Nuclear Magnetic Resonance (NMR) data. This process can be time-consuming and…
Jonathan Fine, Anand Rasjashekar, Gaurav Chopra
We present a deep learning method for identifying all the functional groups of unknown compounds using a combination of FTIR and MS spectra without the use of any database, pre-established rules, procedures, or peak-matching methods. We derive patterns and correlations directly from spectral data representing multiple…
Eric Schulz, Joshua B. Tenenbaum, David Duvenaud, Maarten Speekenbrink + 1 more
How do people recognize and learn about complex functional structure? Taking inspiration from other areas of cognitive science, we propose that this is achieved by harnessing compositionality: complex structure is decomposed into simpler building blocks. We formalize this idea within the framework of Bayesian…
Patryk Burek, Frank Loebe, Heinrich Herre
Background Gene Ontology (GO) is the largest resource for cataloging gene products. This resource grows steadily and, naturally, this growth raises issues regarding the structure of the ontology. Moreover, modeling and refactoring large ontologies such as GO is generally far from being simple, as a whole as well as…
Yongshuai Jiang, Jing Xu, Simeng Hu, Di Liu + 2 more
There are no two identical leaves in the world, so how to find effective markers or features to distinguish them is an important issue. Function transformation, such as f(x,y) and f(x,y,z), can transform two, three, or multiple input/observation variables (in biology, it generally refers to the observed/measured value…