24 papers · ranked by Valyu relevance
Hyeon-Ae Jeon
This review scrutinizes several findings on human hierarchical processing within the prefrontal cortex (PFC) in diverse cognitive domains. Converging evidence from previous studies has shown that the PFC, specifically, BA44, may function as the essential region for hierarchical processing across the domains. In…
Robert Scholz, Arno Villringer, Mauricio J.D. Martins
Humans generate complex hierarchies across a variety of domains, including language and music, and this capacity is often associated with activity in inferior frontal gyrus (IFG). Non-human animals have also been shown to represent simple hierarchies in spatial navigation, and human neuroimaging work has implicated the…
L. Bonetti, G. Fernández Rubio, F. Carlomagno, D. Pantazis + 2 more
Humans extract information from the key features of the physical word, namely space and time. However, while much is known about the neural processing of visuospatial patterns, there is little information on the hierarchical brain mechanisms underlying conscious recognition of auditory sequences extended over time and…
Brian Mozaffari
Based on the notion that the brain is equipped with a hierarchical organization, which embodies environmental contingencies across many time scales, this paper suggests that the medial temporal lobe (MTL)-located deep in the hierarchy-serves as a bridge connecting supra- to infra-MTL levels. Bridging the upper and…
Ying Fan, Muzhi Wang, Nai Ding, Huan Luo
Working memory (WM) is constructive in nature. Instead of passively retaining information, WM reorganizes complex sequences into hierarchically embedded chunks to overcome capacity limits and facilitate flexible behavior. To investigate the neural mechanisms underlying hierarchical reorganization in WM, we performed…
Authors not listed
This work establishes theoretical foundations for hierarchical quantum-classical algorithm design, where complex problems are decomposed across multiple spatial, temporal, or organizational scales with quantum and classical computation assigned to appropriate levels. We develop a mathematical framework that…
Mauricio J.D. Martins, Roberta Bianco, Daniela Sammler, Arno Villringer
Generation of hierarchical structures, such as the embedding of subordinate elements into larger structures, is a core feature of human cognition. Discrimination of well-formed hierarchies is thought to rely on lateral prefrontal cortex (PFC). However, the brain bases underlying the active generation of new…
Krzysztof J. Cios
DNN are one of the most efficient tools that belong to a broader area called deep learning. DNN process input information in a hierarchical way, where each subsequent level of processing extracts more abstract /global / invariant features. In other words, DNN (semi) automatically learn key features from data and then…
Woosang Lim, Jungsoo Lee, Yongsub Lim, Doo-Hwan Bae + 4 more
'Dae-Shik Kim' 'Kyomin Jung' 'Kewei Chen'] Hierarchical organizations of information processing in the brain networks have been known to exist and widely studied. To find proper hierarchical structures in the macaque brain, the traditional methods need the entire pairwise hierarchical relationships between cortical…
Julien Vezoli, Loïc Magrou, Rainer Goebel, Xiao-Jing Wang + 3 more
Hierarchy is a major organizational principle of the cortex and underscores modern computational theories of cortical function. The local microcircuit amplifies long-distance inter-areal input, which show distance-dependent changes in their laminar profiles. Statistical modeling of these changes in laminar profiles…
Lilian LeVinh, Hanspeter A. Mallot
Humans spontaneously structure spatial environments into a hierarchy of regions. Besides connectivity and boundaries, sensory or functional similarities of landmarks have been shown to influence construction of regions. In natural spaces, regions and places are usually named and these names provide additional cues for…
Anjan Dutta, Pau Riba, Josep Lladós, Alícia Fornés
Despite being very successful within the pattern recognition and machine learning community, graphbased methods are often unusable because of the lack of mathematical operations defined in graph domain. Graph embedding, which maps graphs to a vectorial space, has been proposed as a way to tackle these difficulties…
Verónica Vilaplana
In this paper we propose two saliency models for salient object segmentation based on a hierarchical image segmentation, a tree-like structure that represents regions at different scales from the details to the whole image (e.g. gPb-UCM, BPT). The first model is based on a hierarchy of image partitions. The saliency at…
Martin González, Antonio Sánchez-Pedraza, Rebeca Marfil, Juan A. Rodríguez + 2 more
'Juan A. Rodríguez' 'Antonio Bandera' 'Gonzalo Pajares Martinsanz'] There exist image processing applications, such as tracking or pattern recognition, that are not necessarily precise enough to maintain the same resolution across the whole image sensor. In fact, they must only keep it as high as possible in a…
Amin Fehri, Santiago Velasco-Forero, Fernand Meyer
Image segmentation is the process of partitioning an image into a set of meaningful regions according to some criteria. Hierarchical segmentation has emerged as a major trend in this regard as it favors the emergence of important regions at different scales. On the other hand, many methods allow us to have prior…
Ying Cui, Sébastien Lefèvre, Anne Puissant
Geographic object-based image analysis (GEOBIA) framework has gained increasing interest recently. Following this popular paradigm, we propose a novel multiscale classification approach operating on a hierarchical image representation built from two images at different resolutions. They capture the same scene with…
Marcelo Fonseca Faraj, Christof Schulz
Partitioning a graph into balanced blocks such that few edges run between blocks is a key problem for large-scale distributed processing. A current trend for partitioning huge graphs are streaming algorithms, which use low computational resources. In this work, we present a shared-memory streaming multi-recursive…
Esmaeil Farhang, Ramin Toosi, Behnam Karami, Roxana Koushki + 4 more
To expand our knowledge about the object recognition, it is critical to understand the role of spatial frequency (SF) in an object representation that occurs in the inferior temporal (IT) cortex at the final stage of processing the visual information across the ventral visual pathway. Object categories are being…
Rosemary A. Cowell, Morgan D. Barense, Patrick S. Sadil
Thanks to patients Phineas Gage and Henry Molaison, we have long known that behavioral control depends on the frontal lobes, whereas declarative memory depends on the medial temporal lobes (MTL). For decades, cognitive functions-behavioral control, declarative memory-have served as labels for characterizing the…
Brendan Hall, Michael Keiser
Make-on-demand chemical libraries have drastically increased the reach of molecular docking, with the enumerated ready-to-dock ZINC library approaching 5 billion molecules. While ever-growing libraries result in better-scoring molecules, the computational resources required to dock all of ZINC make this endeavor…
Rina Panigrahy, Li Zhang
There is a vast supply of prior art that study models for mental processes. Some studies in psychology and philosophy approach it from an inner perspective in terms of experiences and percepts. Others such as neurobiology or connectionist-machines approach it externally by viewing the mind as complex circuit of neurons…
Authors not listed
Self-organizing tissues, such as organoids, offer transformative potential beyond healthcare by enabling the sustainable production of advanced materials. Resource scarcity and global warming drive the need for innovative fabrication solutions. This prospective review explores developmental biology as a manufacturing…
Brandon Walker, Nathan Miller, Brett Yang, Dhatri V. L. Penna + 15 more
Rapid generation and evaluation of diverse synthesis pathways play a critical role in exploring a broader chemical space and identifying potent drug candidates. Drug discovery often relies on laborintensive manual processes for retro synthetic route finding, resulting in challenges related to scalability and…
Zachary Humphreys, Xenophon Evangelopoulos, Stavros Gerolymatos, Edward O. Pyzer-Knapp + 1 more
Graph neural networks have recently met huge success in various inference tasks including materials property prediction amongst many others. Nevertheless, having an inherently locally-based representation capacity as they do, global representation of materials' structures can only only be achieved by expanding the…