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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...
January 5, 2017: Human Brain Mapping
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. is a web-accessible neuroinformatics resource that organizes existing data about essential properties of all known neuron types in the rodent hippocampal formation. links evidence supporting the assignment of a property to a type with direct pointers to quotes and figures...
June 9, 2016: Brain Informatics
Sibhghatulla Shaikh, Syed Mohd Danish Rizvi, Tabinda Suhail, Shazi Shakil, Adel M Abuzenadah, Rukhsar Anis, Deeba Naaz, 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...
October 3, 2016: CNS & Neurological Disorders Drug Targets
Sergey M Plis, Anand D Sarwate, Dylan Wood, Christopher Dieringer, Drew Landis, Cory Reed, Sandeep R Panta, Jessica A Turner, Jody M Shoemaker, Kim W Carter, Paul Thompson, Kent Hutchison, Vince D Calhoun
The field of neuroimaging has embraced the need for sharing and collaboration. Data sharing mandates from public funding agencies and major journal publishers have spurred the development of data repositories and neuroinformatics consortia. However, efficient and effective data sharing still faces several hurdles. For example, open data sharing is on the rise but is not suitable for sensitive data that are not easily shared, such as genetics. Current approaches can be cumbersome (such as negotiating multiple data sharing agreements)...
2016: Frontiers in Neuroscience
Sheng Yang, Curtis Tatsuoka, Kaushik Ghosh, Nuria Lacuey-Lecumberri, Samden D Lhatoo, Satya S Sahoo
Recent advances in brain fiber tractography algorithms and diffusion Magnetic Resonance Imaging (MRI) data collection techniques are providing new approaches to study brain white matter connectivity, which play an important role in complex neurological disorders such as epilepsy. Epilepsy affects approximately 50 million persons worldwide and it is often described as a disorder of the cortical network organization. There is growing recognition of the need to better understand the role of brain structural networks in the onset and propagation of seizures in epilepsy using high resolution non-invasive imaging technologies...
2016: AMIA Summits on Translational Science Proceedings
William Grisham, Barbara Lom, Linda Lanyon, Raddy L Ramos
The scale of data being produced in neuroscience at present and in the future creates new and unheralded challenges, outstripping conventional ways of handling, considering, and analyzing data. As neuroinformatics enters into this big data era, a need for a highly trained and perhaps unique workforce is emerging. To determine the staffing needs created by the impending era of big data, a workshop (iNeuro Project) was convened November 13-14, 2014. Participants included data resource providers, bioinformatics/analytics trainers, computer scientists, library scientists, and neuroscience educators...
2016: Frontiers in Neuroinformatics
Karl Friston, Harriet R Brown, Jakob Siemerkus, Klaas E Stephan
Twenty years have passed since the dysconnection hypothesis was first proposed (Friston and Frith, 1995; Weinberger, 1993). In that time, neuroscience has witnessed tremendous advances: we now live in a world of non-invasive neuroanatomy, computational neuroimaging and the Bayesian brain. The genomics era has come and gone. Connectomics and large-scale neuroinformatics initiatives are emerging everywhere. So where is the dysconnection hypothesis now? This article considers how the notion of schizophrenia as a dysconnection syndrome has developed - and how it has been enriched by recent advances in clinical neuroscience...
October 2016: Schizophrenia Research
Satya S Sahoo, Annan Wei, Joshua Valdez, Li Wang, Bilal Zonjy, Curtis Tatsuoka, Kenneth A Loparo, Samden D Lhatoo
The recent advances in neurological imaging and sensing technologies have led to rapid increase in the volume, rate of data generation, and variety of neuroscience data. This "neuroscience Big data" represents a significant opportunity for the biomedical research community to design experiments using data with greater timescale, large number of attributes, and statistically significant data size. The results from these new data-driven research techniques can advance our understanding of complex neurological disorders, help model long-term effects of brain injuries, and provide new insights into dynamics of brain networks...
2016: Frontiers in Neuroinformatics
Mufti Mahmud, Stefano Vassanelli
In recent years multichannel neuronal signal acquisition systems have allowed scientists to focus on research questions which were otherwise impossible. They act as a powerful means to study brain (dys)functions in in-vivo and in in-vitro animal models. Typically, each session of electrophysiological experiments with multichannel data acquisition systems generate large amount of raw data. For example, a 128 channel signal acquisition system with 16 bits A/D conversion and 20 kHz sampling rate will generate approximately 17 GB data per hour (uncompressed)...
2016: Frontiers in Neuroscience
Sakshi Piplani, Prabhakar Kumar Verma, Ajit Kumar
The unequivocal hypotheses about anticonvulsant activity of valproic acid (VPA) have always been a basic hurdle in designing next generation neurotherapeutics, particularly the anti-epileptic drugs. The present study reports about a comprehensive in-silico investigation into qualitative and quantitative binding of VPA and corresponding natural ligands of four major enzymes involved in neurotransmissions, namely-GABA transaminase (GABAt), α-keto glutarate dehydrogenase (α-KGDH), Succinate Semialdehyde dehydrogenase (SSADH) and Glutamate Decarboxylase (GAD), respectively...
July 2016: Biomedicine & Pharmacotherapy, Biomédecine & Pharmacothérapie
Dmitrii I Sukhinin, Andreas K Engel, Paul Manger, Claus C Hilgetag
Databases of structural connections of the mammalian brain, such as CoCoMac ( or BAMS (, are valuable resources for the analysis of brain connectivity and the modeling of brain dynamics in species such as the non-human primate or the rodent, and have also contributed to the computational modeling of the human brain. Another animal model that is widely used in electrophysiological or developmental studies is the ferret; however, no systematic compilation of brain connectivity is currently available for this species...
2016: Frontiers in Neuroinformatics
Maria I Falcon, Viktor Jirsa, Ana Solodkin
PURPOSE OF REVIEW: An exciting advance in the field of neuroimaging is the acquisition and processing of very large data sets (so called 'big data'), permitting large-scale inferences that foster a greater understanding of brain function in health and disease. Yet what we are clearly lacking are quantitative integrative tools to translate this understanding to the individual level to lay the basis for personalized medicine. RECENT FINDINGS: Here we address this challenge through a review on how the relatively new field of neuroinformatics modeling has the capacity to track brain network function at different levels of inquiry, from microscopic to macroscopic and from the localized to the distributed...
August 2016: Current Opinion in Neurology
Maria Inez Falcon, Jeffrey D Riley, Viktor Jirsa, Anthony R McIntosh, E Elinor Chen, Ana Solodkin
We have seen important strides in our understanding of mechanisms underlying stroke recovery, yet effective translational links between basic and applied sciences, as well as from big data to individualized therapies, are needed to truly develop a cure for stroke. We present such an approach using The Virtual Brain (TVB), a neuroinformatics platform that uses empirical neuroimaging data to create dynamic models of an individual's human brain; specifically, we simulate fMRI signals by modeling parameters associated with brain dynamics after stroke...
March 2016: ENeuro
Raymond W Lam, Roumen Milev, Susan Rotzinger, Ana C Andreazza, Pierre Blier, Colleen Brenner, Zafiris J Daskalakis, Moyez Dharsee, Jonathan Downar, Kenneth R Evans, Faranak Farzan, Jane A Foster, Benicio N Frey, Joseph Geraci, Peter Giacobbe, Harriet E Feilotter, Geoffrey B Hall, Kate L Harkness, Stefanie Hassel, Zahinoor Ismail, Francesco Leri, Mario Liotti, Glenda M MacQueen, Mary Pat McAndrews, Luciano Minuzzi, Daniel J Müller, Sagar V Parikh, Franca M Placenza, Lena C Quilty, Arun V Ravindran, Tim V Salomons, Claudio N Soares, Stephen C Strother, Gustavo Turecki, Anthony L Vaccarino, Fidel Vila-Rodriguez, Sidney H Kennedy
BACKGROUND: Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication...
April 16, 2016: BMC Psychiatry
A Lotan, T Lifschytz, B Mernick, O Lory, E Levi, E Ben-Shimol, G Goelman, B Lerer
Many psychiatric disorders are highly heritable and may represent the clinical outcome of early aberrations in the formation of neural networks. The placement of brain connectivity as an 'intermediate phenotype' renders it an attractive target for exploring its interaction with genomics and behavior. Given the complexity of genetic make up and phenotypic heterogeneity in humans, translational studies are indicated. Recently, we demonstrated that a mouse model with heterozygous knockout of the key neurodevelopmental gene Ahi1 displays a consistent stress-resilient phenotype...
March 29, 2016: Molecular Psychiatry
Sandeep R Panta, Runtang Wang, Jill Fries, Ravi Kalyanam, Nicole Speer, Marie Banich, Kent Kiehl, Margaret King, Michael Milham, Tor D Wager, Jessica A Turner, Sergey M Plis, Vince D Calhoun
In this paper we propose a web-based approach for quick visualization of big data from brain magnetic resonance imaging (MRI) scans using a combination of an automated image capture and processing system, nonlinear embedding, and interactive data visualization tools. We draw upon thousands of MRI scans captured via the COllaborative Imaging and Neuroinformatics Suite (COINS). We then interface the output of several analysis pipelines based on structural and functional data to a t-distributed stochastic neighbor embedding (t-SNE) algorithm which reduces the number of dimensions for each scan in the input data set to two dimensions while preserving the local structure of data sets...
2016: Frontiers in Neuroinformatics
Jafri Malin Abdullah
12 months ago the first Neuroscience special issue of the Malaysia Journal of Medical Sciences was born with the intention to increase the number of local publication dedicated to neurosciences. Since then many events happened in the neuroscience world of Malaysia, those considered major were the establishment of a Neurotechnology Foresight 2050 task force by the Academy of Medicine Malaysia as well as the launching of Malaysia as the 18th member to join the International Neuroinformatics Coordinating Facility on the 9th October 2015 which was officiated by the Deputy Ministers of Higher Education, Datuk Mary Yap...
December 2015: Malaysian Journal of Medical Sciences: MJMS
Makoto Takemiya, Kei Majima, Mitsuaki Tsukamoto, Yukiyasu Kamitani
Data-driven neuroscience aims to find statistical relationships between brain activity and task behavior from large-scale datasets. To facilitate high-throughput data processing and modeling, we created BrainLiner as a web platform for sharing time-aligned, brain-behavior data. Using an HDF5-based data format, BrainLiner treats brain activity and data related to behavior with the same salience, aligning both behavioral and brain activity data on a common time axis. This facilitates learning the relationship between behavior and brain activity...
2016: Frontiers in Neuroinformatics
Jose Luis Ambite, Marcelo Tallis, Kathryn Alpert, David B Keator, Margaret King, Drew Landis, George Konstantinidis, Vince D Calhoun, Steven G Potkin, Jessica A Turner, Lei Wang
In many scientific domains, including neuroimaging studies, there is a need to obtain increasingly larger cohorts to achieve the desired statistical power for discovery. However, the economics of imaging studies make it unlikely that any single study or consortia can achieve the desired sample sizes. What is needed is an architecture that can easily incorporate additional studies as they become available. We present such architecture based on a virtual data integration approach, where data remains at the original sources, and is retrieved and harmonized in response to user queries...
July 2015: Data Integration in the Life Sciences: ... International Workshop, DILS ...: Proceedings. DILS (Conference)
Erik De Schutter
No abstract text is available yet for this article.
January 2016: Neuroinformatics
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