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system quanta as discrete units of behavior
system quanta as discrete units of behavior

... Trigger mechanisms. The activity of system quantum originates after excitability of elements forming it achieves certain critical level (Fig. 2). Activity of system quanta proceeds until the initial need is satisfied. The most investigated are the trigger mechanisms of system quanta of behavior. Bi ...
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... We are in the midst of a golden era of neuroscience, with the integration of neurophysiological and theoretical techniques yielding rapid advances in our understanding of the neural mechanisms underlying perception and cognition. Neurophysiological experiments have provided a wealth of information o ...
Design and Analysis of Genetic Studies After the Hapmap Project
Design and Analysis of Genetic Studies After the Hapmap Project

... from 10-35% more SNPs, beyond the minimal tag SNP set from the first population, need to be genotyped in the second population to reach the same power. Gopalakrishnan et al. apply yet a third algorithm, called FESTA, to infer the number of tag SNPs needed for whole genome association testing, and th ...
Neuroanatomical correlates of intelligence
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The Seven Types of ADD - Neighbors Helping Neighbors
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Cellular localization of RNA expression in central and peripheral
Cellular localization of RNA expression in central and peripheral

... CB2R mRNA in DA neurons. They performed dual ISH using a CB2 probe to detect their target and a tyrosine hydroxylase (TH) probe to identify the phenotype of the CB2 -positive neurons (Figures 10 and 11). The findings of Zhang et al. completely change the view that brain CB2Rs are not expressed in ne ...
biological bases of behavior
biological bases of behavior

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Decoupling Neural Networks From Reality: Dissociative Experiences
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Time representation in reinforcement learning models of

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1 An Agile ETL Data Development An Agile Extract Transform and

... services and other application areas, most enterprise systems in organisations continue to store and manage data using traditional relational databases. The ANU is no exception in this respect. Most of the data required for the ERA submission is stored, collected, or uploaded into the ANU's Research ...
Serre-Poggio_ACM_R2_finalSubmission
Serre-Poggio_ACM_R2_finalSubmission

... It has been argued that vision is a form of intelligence: it is suggestive that the sentence ‘I see’ is often used to mean ‘I understand’! Our visual cortex may serve as a proxy for the rest of the cortex and thus for intelligence itself. There is little doubt that even a partial solution to the que ...
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Neuroinformatics

Neuroinformatics is a research field concerned with the organization of neuroscience data by the application of computational models and analytical tools. These areas of research are important for the integration and analysis of increasingly large-volume, high-dimensional, and fine-grain experimental data. Neuroinformaticians provide computational tools, mathematical models, and create interoperable databases for clinicians and research scientists. Neuroscience is a heterogeneous field, consisting of many and various sub-disciplines (e.g., Cognitive Psychology, Behavioral Neuroscience, and Behavioral Genetics). In order for our understanding of the brain to continue to deepen, it is necessary that these sub-disciplines are able to share data and findings in a meaningful way; Neuroinformaticians facilitate this.Neuroinformatics stands at the intersection of neuroscience and information science. Other fields, like genomics, have demonstrated the effectiveness of freely-distributed databases and the application of theoretical and computational models for solving complex problems. In Neuroinformatics, such facilities allow researchers to more easily quantitatively confirm their working theories by computational modeling. Additionally, neuroinformatics fosters collaborative research—an important fact that facilitates the field's interest in studying the multi-level complexity of the brain.There are three main directions where neuroinformatics has to be applied: the development of tools and databases for management and sharing of neuroscience data at all levels of analysis, the development of tools for analyzing and modeling neuroscience data, the development of computational models of the nervous system and neural processes.In the recent decade, as vast amounts of diverse data about the brain were gathered by many research groups, the problem was raised of how to integrate the data from thousands of publications in order to enable efficient tools for further research. The biological and neuroscience data are highly interconnected and complex, and by itself, integration represents a great challenge for scientists.Combining informatics research and brain research provides benefits for both fields of science. On one hand, informatics facilitates brain data processing and data handling, by providing new electronic and software technologies for arranging databases, modeling and communication in brain research. On the other hand, enhanced discoveries in the field of neuroscience will invoke the development of new methods in information technologies (IT).
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