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Neuroinformatics

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https://www.readbyqxmd.com/read/29926817/how-random-is-the-random-forest-random-forest-algorithm-on-the-service-of-structural-imaging-biomarkers-for-alzheimer-s-disease-from-alzheimer-s-disease-neuroimaging-initiative-adni-database
#1
REVIEW
Stavros I Dimitriadis, Dimitris Liparas
Neuroinformatics is a fascinating research field that applies computational models and analytical tools to high dimensional experimental neuroscience data for a better understanding of how the brain functions or dysfunctions in brain diseases. Neuroinformaticians work in the intersection of neuroscience and informatics supporting the integration of various sub-disciplines (behavioural neuroscience, genetics, cognitive psychology, etc.) working on brain research. Neuroinformaticians are the pathway of information exchange between informaticians and clinicians for a better understanding of the outcome of computational models and the clinical interpretation of the analysis...
June 2018: Neural Regeneration Research
https://www.readbyqxmd.com/read/29924904/neuroinformatics-and-computational-modelling-as-complementary-tools-for-neurotoxicology-studies
#2
Marja-Leena Linne
Neuroinformatics is an area of science that aims to integrate neuroscience data and develop modern computational tools to increase our understanding of the functions of the nervous system in health and disease. Neuroinformatics tools include, among others, databases for storing and sharing data, repositories for managing documents and source code, and software tools for analysing, modelling and simulating signals and images. This MiniReview aims to present the state-of-the-art in neuroinformatics and computational in silico modelling of neurobiological processes and neuroscientific phenomena as well as to discuss the use of in silico models in neurotoxicology research...
June 20, 2018: Basic & Clinical Pharmacology & Toxicology
https://www.readbyqxmd.com/read/29911173/modeling-brain-dynamics-in-brain-tumor-patients-using-the-virtual-brain
#3
Hannelore Aerts, Michael Schirner, Ben Jeurissen, Dirk Van Roost, Eric Achten, Petra Ritter, Daniele Marinazzo
Presurgical planning for brain tumor resection aims at delineating eloquent tissue in the vicinity of the lesion to spare during surgery. To this end, noninvasive neuroimaging techniques such as functional MRI and diffusion-weighted imaging fiber tracking are currently employed. However, taking into account this information is often still insufficient, as the complex nonlinear dynamics of the brain impede straightforward prediction of functional outcome after surgical intervention. Large-scale brain network modeling carries the potential to bridge this gap by integrating neuroimaging data with biophysically based models to predict collective brain dynamics...
May 2018: ENeuro
https://www.readbyqxmd.com/read/29881339/new-protocol-for-quantitative-analysis-of-brain-cortex-electroencephalographic-activity-in-patients-with-psychiatric-disorders
#4
Grzegorz M Wojcik, Jolanta Masiak, Andrzej Kawiak, Piotr Schneider, Lukasz Kwasniewicz, Nikodem Polak, Anna Gajos-Balinska
The interview is still the main and most important tool in psychiatrist's work. The neuroimaging methods such as CT or MRI are widely used in other fields of medicine, for instance neurology. However, psychiatry lacks effective quantitative methods to support of diagnosis. A novel neuroinformatic approach to help clinical patients by means of electroencephalographic technology in order to build foundations for finding neurophysiological biomarkers of psychiatric disorders is proposed. A cohort of 30 right-handed patients (21 males, 9 females) with psychiatric disorders (mainly with panic and anxiety disorder, Asperger syndrome as well as with phobic anxiety disorders, schizophrenia, bipolar affective disorder, obsessive-compulsive disorder, nonorganic hypersomnia, and moderate depressive episode) were examined using the dense array EEG amplifier in the P300 experiment...
2018: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/29876420/collection-of-human-reaction-times-and-supporting-health-related-data-for-analysis-of-cognitive-and-physical-performance
#5
Petr Brůha, Roman Mouček, Vítězslav Vacek, Pavel Šnejdar, Kateřina Černá, Petr Řehoř
Smoking, excessive drinking, overeating and physical inactivity are well-established risk factors decreasing human physical performance. Moreover, epidemiological work has identified modifiable lifestyle factors, such as poor diet and physical and cognitive inactivity that are associated with the risk of reduced cognitive performance. Definition, collection and annotation of human reaction times and suitable health related data and metadata provides researchers with a necessary source for further analysis of human physical and cognitive performance...
April 2018: Data in Brief
https://www.readbyqxmd.com/read/29875648/brain-code-a-secure-neuroinformatics-platform-for-management-federation-sharing-and-analysis-of-multi-dimensional-neuroscience-data
#6
Anthony L Vaccarino, Moyez Dharsee, Stephen Strother, Don Aldridge, Stephen R Arnott, Brendan Behan, Costas Dafnas, Fan Dong, Kenneth Edgecombe, Rachad El-Badrawi, Khaled El-Emam, Tom Gee, Susan G Evans, Mojib Javadi, Francis Jeanson, Shannon Lefaivre, Kristen Lutz, F Chris MacPhee, Jordan Mikkelsen, Tom Mikkelsen, Nicholas Mirotchnick, Tanya Schmah, Christa M Studzinski, Donald T Stuss, Elizabeth Theriault, Kenneth R Evans
Historically, research databases have existed in isolation with no practical avenue for sharing or pooling medical data into high dimensional datasets that can be efficiently compared across databases. To address this challenge, the Ontario Brain Institute's "Brain-CODE" is a large-scale neuroinformatics platform designed to support the collection, storage, federation, sharing and analysis of different data types across several brain disorders, as a means to understand common underlying causes of brain dysfunction and develop novel approaches to treatment...
2018: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/29718199/boutiques-a-flexible-framework-to-integrate-command-line-applications-in-computing-platforms
#7
Tristan Glatard, Gregory Kiar, Tristan Aumentado-Armstrong, Natacha Beck, Pierre Bellec, Rémi Bernard, Axel Bonnet, Shawn T Brown, Sorina Camarasu-Pop, Frédéric Cervenansky, Samir Das, Rafael Ferreira da Silva, Guillaume Flandin, Pascal Girard, Krzysztof J Gorgolewski, Charles R G Guttmann, Valérie Hayot-Sasson, Pierre-Olivier Quirion, Pierre Rioux, Marc-Étienne Rousseau, Alan C Evans
We present Boutiques, a system to automatically publish, integrate, and execute command-line applications across computational platforms. Boutiques applications are installed through software containers described in a rich and flexible JSON language. A set of core tools facilitates the construction, validation, import, execution, and publishing of applications. Boutiques is currently supported by several distinct virtual research platforms, and it has been used to describe dozens of applications in the neuroinformatics domain...
May 1, 2018: GigaScience
https://www.readbyqxmd.com/read/29704208/neuroimaging-neuroinformatics-sample-size-and-other-evolutionary-topics
#8
EDITORIAL
David N Kennedy
No abstract text is available yet for this article.
April 2018: Neuroinformatics
https://www.readbyqxmd.com/read/29627437/feature-selection-for-the-classification-of-traced-neurons
#9
José D López-Cabrera, Juan V Lorenzo-Ginori
BACKGROUND: The great availability of computational tools to calculate the properties of traced neurons leads to the existence of many descriptors which allow the automated classification of neurons from these reconstructions. This situation determines the necessity to eliminate irrelevant features as well as making a selection of the most appropriate among them, in order to improve the quality of the classification obtained. METHODS: The dataset used contains a total of 318 traced neurons, classified by human experts in 192 GABAergic interneurons and 126 pyramidal cells...
June 1, 2018: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/29599715/dynasim-a-matlab-toolbox-for-neural-modeling-and-simulation
#10
Jason S Sherfey, Austin E Soplata, Salva Ardid, Erik A Roberts, David A Stanley, Benjamin R Pittman-Polletta, Nancy J Kopell
DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations...
2018: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/29508123/a-bit-encoding-based-new-data-structure-for-time-and-memory-efficient-handling-of-spike-times-in-an-electrophysiological-setup
#11
Bengt Ljungquist, Per Petersson, Anders J Johansson, Jens Schouenborg, Martin Garwicz
Recent neuroscientific and technical developments of brain machine interfaces have put increasing demands on neuroinformatic databases and data handling software, especially when managing data in real time from large numbers of neurons. Extrapolating these developments we here set out to construct a scalable software architecture that would enable near-future massive parallel recording, organization and analysis of neurophysiological data on a standard computer. To this end we combined, for the first time in the present context, bit-encoding of spike data with a specific communication format for real time transfer and storage of neuronal data, synchronized by a common time base across all unit sources...
March 5, 2018: Neuroinformatics
https://www.readbyqxmd.com/read/29435954/large-scale-exploration-of-neuronal-morphologies-using-deep-learning-and-augmented-reality
#12
Zhongyu Li, Erik Butler, Kang Li, Aidong Lu, Shuiwang Ji, Shaoting Zhang
Recently released large-scale neuron morphological data has greatly facilitated the research in neuroinformatics. However, the sheer volume and complexity of these data pose significant challenges for efficient and accurate neuron exploration. In this paper, we propose an effective retrieval framework to address these problems, based on frontier techniques of deep learning and binary coding. For the first time, we develop a deep learning based feature representation method for the neuron morphological data, where the 3D neurons are first projected into binary images and then learned features using an unsupervised deep neural network, i...
February 12, 2018: Neuroinformatics
https://www.readbyqxmd.com/read/29069078/transcriptomic-correlates-of-neuron-electrophysiological-diversity
#13
Shreejoy J Tripathy, Lilah Toker, Brenna Li, Cindy-Lee Crichlow, Dmitry Tebaykin, B Ogan Mancarci, Paul Pavlidis
How neuronal diversity emerges from complex patterns of gene expression remains poorly understood. Here we present an approach to understand electrophysiological diversity through gene expression by integrating pooled- and single-cell transcriptomics with intracellular electrophysiology. Using neuroinformatics methods, we compiled a brain-wide dataset of 34 neuron types with paired gene expression and intrinsic electrophysiological features from publically accessible sources, the largest such collection to date...
October 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/29067311/mnemonic-strategy-training-of-the-elderly-at-risk-for-dementia-enhances-integration-of-information-processing-via-cross-frequency-coupling
#14
Stavros I Dimitriadis, Ioannis Tarnanas, Mark Wiederhold, Brenda Wiederhold, Magda Tsolaki, Elgar Fleisch
INTRODUCTION: We sought to identify whether intensive 10-week mobile health mnemonic strategy training (MST) could shift the resting-state brain network more toward cortical-level integration, which has recently been proven to reflect the reorganization of the brain networks compensating the cognitive decline. METHODS: One hundred fifty-eight patients with mild cognitive impairment (MCI) were selected and participated in 10-week training lasting 90 min/d of memory training...
November 2016: Alzheimer's & Dementia: Translational Research & Clinical Interventions
https://www.readbyqxmd.com/read/28664183/the-virtual-mouse-brain-a-computational-neuroinformatics-platform-to-study-whole-mouse-brain-dynamics
#15
Francesca Melozzi, Marmaduke M Woodman, Viktor K Jirsa, Christophe Bernard
Connectome-based modeling of large-scale brain network dynamics enables causal in silico interrogation of the brain's structure-function relationship, necessitating the close integration of diverse neuroinformatics fields. Here we extend the open-source simulation software The Virtual Brain (TVB) to whole mouse brain network modeling based on individual diffusion magnetic resonance imaging (dMRI)-based or tracer-based detailed mouse connectomes. We provide practical examples on how to use The Virtual Mouse Brain (TVMB) to simulate brain activity, such as seizure propagation and the switching behavior of the resting state dynamics in health and disease...
May 2017: ENeuro
https://www.readbyqxmd.com/read/28549853/molecular-fingerprinting-of-principal-neurons-in-the-rodent-hippocampus-a-neuroinformatics-approach
#16
D J Hamilton, C M White, C L Rees, D W Wheeler, G A Ascoli
Neurons are often classified by their morphological and molecular properties. The online knowledge base Hippocampome.org primarily defines neuron types from the rodent hippocampal formation based on their main neurotransmitter (glutamate or GABA) and the spatial distributions of their axons and dendrites. For each neuron type, this open-access resource reports any and all published information regarding the presence or absence of known molecular markers, including calcium-binding proteins, neuropeptides, receptors, channels, transcription factors, and other molecules of biomedical relevance...
September 10, 2017: Journal of Pharmaceutical and Biomedical Analysis
https://www.readbyqxmd.com/read/28381924/we-must-invest-in-applied-knowledge-of-computational-neurosciences-and-neuroinformatics-as-an-important-future-in-malaysia-the-malaysian-brain-mapping-project
#17
EDITORIAL
Putra Sumari, Zamzuri Idris, Jafri Malin Abdullah
The Academy of Sciences Malaysia and the Malaysian Industry-Government group for High Technology has been working hard to project the future of big data and neurotechnology usage up to the year 2050. On the 19 September 2016, the International Brain Initiative was announced by US Under Secretary of State Thomas Shannon at a meeting that accompanied the United Nations' General Assembly in New York City. This initiative was seen as an important effort but deemed costly for developing countries. At a concurrent meeting hosted by the US National Science Foundation at Rockefeller University, numerous countries discussed this massive project, which would require genuine collaboration between investigators in the realms of neuroethics...
March 2017: Malaysian Journal of Medical Sciences: MJMS
https://www.readbyqxmd.com/read/28054725/mapping-complementary-features-of-cross-species-structural-connectivity-to-construct-realistic-virtual-brains
#18
Gleb Bezgin, Ana Solodkin, Rembrandt Bakker, Petra Ritter, Anthony R McIntosh
Modern systems neuroscience increasingly leans on large-scale multi-lab neuroinformatics initiatives to provide necessary capacity for biologically realistic modeling of primate whole-brain activity. Here, we present a framework to assemble primate brain's biologically plausible anatomical backbone for such modeling initiatives. In this framework, structural connectivity is determined by adding complementary information from invasive macaque axonal tract tracing and non-invasive human diffusion tensor imaging...
April 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/27747821/name-calling-in-the-hippocampus-and-beyond-coming-to-terms-with-neuron-types-and-properties
#19
D J Hamilton, D W Wheeler, C M White, C L Rees, A O Komendantov, M Bergamino, G A Ascoli
Widely spread naming inconsistencies in neuroscience pose a vexing obstacle to effective communication within and across areas of expertise. This problem is particularly acute when identifying neuron types and their properties. Hippocampome.org is a web-accessible neuroinformatics resource that organizes existing data about essential properties of all known neuron types in the rodent hippocampal formation. Hippocampome.org links evidence supporting the assignment of a property to a type with direct pointers to quotes and figures...
March 2017: Brain Informatics
https://www.readbyqxmd.com/read/27697060/prediction-of-anti-diabetic-drugs-as-dual-inhibitors-against-acetylcholinesterase-and-beta-secretase-a-neuroinformatics-study
#20
Sibhghatulla Shaikh, Syed Mohd Danish Rizvi, Tabinda Suhail, Shazi Shakil, Adel M Abuzenadah, Rukhsar Anis, Deeba Naaz, Ashraf Dallol, Mohd Haneef, Adnan Ahmad, Latafat Choudhary
An increasing number of research evidences indicate linkage between type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD); the two most common diseases of aging. In addition, T2DM and AD also share some common pathophysiological features. Therefore, dual therapy that targets both the diseases can be regarded as a beneficial approach. Acetylcholinesterase (AChE) and beta-secretase (BACE) have been considered as potential therapeutic targets for AD. Accordingly, the piece of work presented here describes the binding of anti-diabetic drugs (Jardiance, Suiny and Nesina) with AChE and BACE so as to further investigate connecting bridges concerning the treatment of these two diseases...
2016: CNS & Neurological Disorders Drug Targets
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