130,361 research outputs found
A Contour Based Automatic Method to Classify Local Field Potentials Recorded from Rat Barrel Cortex
No full textWhisking is the natural way for the rodents to explore the environment. Using the Local Field Potentials (LFPs) recorded from the barrel columns of the rat somatosensory cortex (S1) is one of the ways to extract information about the signal processing pathway during tactile information processing. Studies have shown that intra-and trans-columnar microcircuits in the barrel cortex segregate and integrate information during this pathway activation. During each experiment many single sweeps (sometimes referred as raw traces) of signal are recorded as a result of underlying network activity and averaged to extract information from them. However, mostly these single sweeps are very different in their shapes and extracting the information provided by the shape is the most common way to decode the transmitted information about the network. In this work, we propose a method capable of classifying these single sweeps from an experiment based on their shapes. The shape specific information of the single sweeps provided by this method can be used in decoding the tactile information processing pathway with a higher precision
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An Automated Classification Method for Single Sweep Local Field Potentials Recorded from Rat Barrel Cortex under Mechanical Whisker Stimulation
No full textUnderstanding brain signals as an outcome of the brain's information processing is a challenge for the neuroscience and neuroengineering community. Rodents sense and explore the environment through whisking. The local field potentials (LFPs) recorded from the barrel columns of the rat somatosensory cortex during whisking provide information about the tactile information processing pathway. Particularly when large-scale high-resolution neuronal probes are used, during each experiment many single LFPs are recorded as an outcome of the underlying neuronal network activation and averaged to extract information. However, single LFP signals are frequently very different from each other. Extracting information provided by their shape can be used to better decode information transmitted by the network. This work proposes an automated method capable of classifying these signals based on their shapes. A template matching approach is used to recognize single LFPs and the contour information is extracted from the recognized signals to generate a feature matrix, which is then classified using intelligent K-means clustering. As an application example, the shape-specific information (e.g., latency and amplitude) of LFPs evoked in the rat barrel cortex are used in decoding the rat whisker information processing pathway using the proposed method
An Automated Method for Clustering Single Sweep Local Field Potentials Recorded from Rat Barrel Cortex
No full textMeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Scholarly Communication and Publishing Lunch and Learn Talk #11: The ULS Open Access Author Fee Fund
No full textAt the May 2014 talk, you will learn about the ULS Open Access Author Fee Fund--what it is, why we do it, how it works, and how the program is going so far
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