scholarly journals 46. Effort, Avolition, and Function in Schizophrenia: Analysis of Behavioral and Neuroimaging Data With Relationships to Real-World Function

2017 ◽  
Vol 43 (suppl_1) ◽  
pp. S25-S25
Author(s):  
Adam Culbreth ◽  
Erin Moran ◽  
Andrew Westbrook ◽  
Julia Sheffield ◽  
Deanna Barch
Keyword(s):  
Real World ◽  
Neuroimaging Data ◽  
And Function ◽  
World Function

Age and Perceptions of Usability on Telephone Menu Systems

2002 ◽  
Vol 46 (2) ◽  
pp. 175-179 ◽  
Author(s):  
Christopher Reynolds ◽  
Sara J. Czaja ◽  
Joseph Sharit
Keyword(s):  
Older Adults ◽  
Real World ◽  
Community Dwelling ◽  
Relative Importance ◽  
Menu System ◽  
And Function ◽  
Sample Set

The objectives of this study were to determine if older adults encounter difficulty using real-world telephone menu system applications and to gather data on the usability features of these systems. Six real-world telephone menu systems, which varied in complexity and function, were examined. The sample included 32 community dwelling adults ranging in age from 18–80 years. Participants interacted with the menu systems to perform a sample set of tasks. They were also asked to rate the usability features of the system in terms of their goodness and their relative importance. The data indicated that in addition to taking longer, the older adults tended to have more difficulty performing the tasks. The findings also indicated that memorability was an important usability feature, and that the ratings of overall usability and overall satisfaction were significantly worse for the older adults.

scholarly journals Cognitive Network Neuroscience

2015 ◽  
Vol 27 (8) ◽  
pp. 1471-1491 ◽  
Author(s):  
John D. Medaglia ◽  
Mary-Ellen Lynall ◽  
Danielle S. Bassett
Keyword(s):  
Cognitive Neuroscience ◽  
Network Science ◽  
Structural Connectivity ◽  
Cognitive Network ◽  
Network Characteristics ◽  
Time Dynamics ◽  
Neuroimaging Data ◽  
Control Learning ◽  
And Function ◽  
Network Neuroscience

Network science provides theoretical, computational, and empirical tools that can be used to understand the structure and function of the human brain in novel ways using simple concepts and mathematical representations. Network neuroscience is a rapidly growing field that is providing considerable insight into human structural connectivity, functional connectivity while at rest, changes in functional networks over time (dynamics), and how these properties differ in clinical populations. In addition, a number of studies have begun to quantify network characteristics in a variety of cognitive processes and provide a context for understanding cognition from a network perspective. In this review, we outline the contributions of network science to cognitive neuroscience. We describe the methodology of network science as applied to the particular case of neuroimaging data and review its uses in investigating a range of cognitive functions including sensory processing, language, emotion, attention, cognitive control, learning, and memory. In conclusion, we discuss current frontiers and the specific challenges that must be overcome to integrate these complementary disciplines of network science and cognitive neuroscience. Increased communication between cognitive neuroscientists and network scientists could lead to significant discoveries under an emerging scientific intersection known as cognitive network neuroscience.

scholarly journals A Knowledge Representation and Reasoning System for Multimodal Neuroimaging Studies

2017 ◽  
Vol 20 (59) ◽  
pp. 42 ◽  
Author(s):  
Ana Coelho ◽  
Paulo Marques ◽  
Ricardo Magalhães ◽  
Nuno Sousa ◽  
José Neves ◽  
...  
Keyword(s):  
Knowledge Representation And Reasoning ◽  
Case Based Reasoning ◽  
Multimodal Neuroimaging ◽  
Multimodal Data ◽  
Reasoning System ◽  
Reasoning Systems ◽  
Major Interest ◽  
Neuroimaging Data ◽  
And Function ◽  
Undiagnosed Diseases

Multimodal neuroimaging analyses are of major interest for both research and clinical practice, enabling the combined evaluation of the structure and function of the human brain. These analyses generate large volumes of data and consequently increase the amount of possibly useful information. Indeed, BrainArchive was developed in order to organize, maintain and share this complex array of neuroimaging data. It stores all the information available for each participant/patient, being dynamic by nature. Notably, the application of reasoning systems to this multimodal data has the potential to provide tools for the identification of undiagnosed diseases. As a matter of fact, in this work we explore how Artificial Intelligence techniques for decision support work, namely Case-Based Reasoning (CBR) that may be used to achieve such endeavour. Particularly, it is proposed a reasoning system that uses the information stored in BrainArchive as past knowledge for the identification of individuals that are at risk of contracting some brain disease.

Dual-acting agents for improving cognition and real-world function in Alzheimer’s disease: Focus on 5-HT6 and D3 receptors as hubs

2020 ◽  
Vol 177 ◽  
pp. 108099 ◽  
Author(s):  
Mark J. Millan ◽  
Anne Dekeyne ◽  
Alain Gobert ◽  
Mauricette Brocco ◽  
Clotilde Mannoury la Cour ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Real World ◽  
D3 Receptors ◽  
Disease Focus ◽  
World Function

scholarly journals Reconstructing ribosomal genes from large scale total RNA meta-transcriptomic data

2020 ◽  
Vol 36 (11) ◽  
pp. 3365-3371
Author(s):  
Yaxin Xue ◽  
Anders Lanzén ◽  
Inge Jonassen
Keyword(s):  
Microbial Communities ◽  
Real World ◽  
Structure And Function ◽  
Rrna Genes ◽  
Supplementary Information ◽  
Metagenomic Data ◽  
Total Rna ◽  
Transcriptomic Data ◽  
And Function ◽  
Complex Datasets

Abstract Motivation Technological advances in meta-transcriptomics have enabled a deeper understanding of the structure and function of microbial communities. ‘Total RNA’ meta-transcriptomics, sequencing of total reverse transcribed RNA, provides a unique opportunity to investigate both the structure and function of active microbial communities from all three domains of life simultaneously. A major step of this approach is the reconstruction of full-length taxonomic marker genes such as the small subunit ribosomal RNA. However, current tools for this purpose are mainly targeted towards analysis of amplicon and metagenomic data and thus lack the ability to handle the massive and complex datasets typically resulting from total RNA experiments. Results In this work, we introduce MetaRib, a new tool for reconstructing ribosomal gene sequences from total RNA meta-transcriptomic data. MetaRib is based on the popular rRNA assembly program EMIRGE, together with several improvements. We address the challenge posed by large complex datasets by integrating sub-assembly, dereplication and mapping in an iterative approach, with additional post-processing steps. We applied the method to both simulated and real-world datasets. Our results show that MetaRib can deal with larger datasets and recover more rRNA genes, which achieve around 60 times speedup and higher F1 score compared to EMIRGE in simulated datasets. In the real-world dataset, it shows similar trends but recovers more contigs compared with a previous analysis based on random sub-sampling, while enabling the comparison of individual contig abundances across samples for the first time. Availability and implementation The source code of MetaRib is freely available at https://github.com/yxxue/MetaRib. Contact [email protected] or [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Neural signal during immediate reward anticipation in schizophrenia: Relationship to real-world motivation and function

2015 ◽  
Vol 9 ◽  
pp. 153-163 ◽  
Author(s):  
Karuna Subramaniam ◽  
Christine I. Hooker ◽  
Bruno Biagianti ◽  
Melissa Fisher ◽  
Srikantan Nagarajan ◽  
...  
Keyword(s):  
Real World ◽  
Neural Signal ◽  
Reward Anticipation ◽  
And Function

scholarly journals A practical guide to linking brain-wide gene expression and neuroimaging data

2018 ◽  
Author(s):  
Aurina Arnatkevičiūtė ◽  
Ben D. Fulcher ◽  
Alex Fornito
Keyword(s):  
Gene Expression ◽  
Brain Atlas ◽  
Expression Data ◽  
Analysis Pipeline ◽  
Atlas Data ◽  
Processing Pipeline ◽  
Neuroimaging Data ◽  
Brain Structure And Function ◽  
Expression Atlas ◽  
And Function

AbstractThe recent availability of comprehensive, brain-wide gene expression atlases such as the Allen Human Brain Atlas (AHBA) has opened new opportunities for understanding how spatial variations on the molecular scale relate to the macroscopic neuroimaging phenotypes. A rapidly growing body of literature is demonstrating relationships between gene expression and diverse properties of brain structure and function, but approaches for combining expression atlas data with neuroimaging are highly inconsistent, with substantial variations in how the expression data are processed. The degree to which these methodological variations affect findings is unclear. Here, we outline a seven-step analysis pipeline for relating brain-wide transcriptomic and neuroimaging data and compare how different processing choices influence the resulting data. We suggest that studies using AHBA should work towards a unified data processing pipeline to ensure consistent and reproducible results in this burgeoning field.

scholarly journals Designing and coding with BBC micro:bit to solve a real-world task – a challenging movement between contexts

2021 ◽  
Author(s):  
A-M. Cederqvist
Keyword(s):  
Design Process ◽  
Real World ◽  
Structure And Function ◽  
Educational Content ◽  
Dual Nature ◽  
The Real ◽  
And Function ◽  
Point Of Departure ◽  
Critical Aspects

AbstractDesigning programmed technological solutions (PTS) with programming materials has become a way to contextualise educational content related to PTS and programming. However, studies show that pupils have difficulties conceptualising central phenomena involved in the process, which affects their ability to design PTS. In order to understand these difficulties, this study investigates pupils’ ways of experiencing the process of solving a real-world task with a programming material. The study takes its point of departure from a previous study that identified two central phenomena, the dual nature (structure and function) of PTS and the BBC micro:bit material, when pupils, aged 10 and 14, were designing a burglar alarm with the BBC micro:bit. The data was revisited with the aim of analysing pupils’ sequential discernment of critical aspects of the phenomena (i.e. aspects necessary to discern in order to understand phenomena), and how this affects how the design process unfolds. The results show that the movement from the real-world context toward the BBC micro:bit context is challenging. Pupils need to be able to connect conditions in the real-world context both to aspects of the dual nature of their PTS, and to aspects of the BBC micro:bit material that represent the dual nature. This suggests the importance of appreciating the BBC micro:bit context and the real-world context in relation to the dual nature of PTS, and of addressing the sequential stages of the process in which aspects of phenomena and their interrelations are emphasised, to help pupils see the PTS in the changing contexts.

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