A mosaic of sex-related structural changes in the human brain following exposure to real-life stress

2019 ◽  
Vol 225 (1) ◽  
pp. 461-466 ◽  
Author(s):  
Guy Shalev ◽  
Roee Admon ◽  
Zohar Berman ◽  
Daphna Joel
2009 ◽  
Author(s):  
Dmitry Alekseevich Dimitriev ◽  
E. V. Saperova ◽  
Y. D. Karpenko
Keyword(s):  

Author(s):  
Guaracy Silveira

Guided by the principles of digital game design, the author proposes a reformulation of the pedagogical objectives and focuses of the pedagogical graduate courses, especially in relation to internship and training stages, in a problem-solving model based on digital games intending to shift the formation of future teachers from an abstract model to a real-life-based problem, thus proposing guidelines for an interdisciplinary project. The chapter summaries this proposal enlisting the necessary structural changes needed to achieve this goal to guide those wishing to adjust their pedagogical projects in a way to insert the digital games as educational devices in their courses without having to remodel the entire existing course. An introduction to the problem is made, its theorical background presented, followed by a contextualization of the Brazilian educational area with the proposition delineated and a conclusion.


Hypertension ◽  
2002 ◽  
Vol 39 (1) ◽  
pp. 184-188 ◽  
Author(s):  
Daniela Lucini ◽  
Guido Norbiato ◽  
Mario Clerici ◽  
Massimo Pagani

1953 ◽  
Vol 17 (5) ◽  
pp. 355-358 ◽  
Author(s):  
David Berger
Keyword(s):  

Life Sciences ◽  
2016 ◽  
Vol 148 ◽  
pp. 254-259 ◽  
Author(s):  
Kazunari Tominaga ◽  
Yoshiko Fujikawa ◽  
Fumio Tanaka ◽  
Noriko Kamata ◽  
Hirokazu Yamagami ◽  
...  

Author(s):  
Aleksejs Zorins ◽  
Peteris Grabusts

<p class="R-AbstractKeywords">There are numerous applications of Artificial Neural Networks (ANN) at the present time and there are different learning algorithms, topologies, hybrid methods etc. It is strongly believed that ANN is built using human brain’s functioning principles but still ANN is very primitive and tricky way for real problem solving. In the recent years modern neurophysiology advanced to a big extent in understanding human brain functions and structure, however, there is a lack of this knowledge application to real ANN learning algorithms. Each learning algorithm and each network topology should be carefully developed to solve more or less complex problem in real life. One may say that almost each serious application requires its own network topology, algorithm and data pre-processing. This article presents a survey of several ways to improve ANN learning possibilities according to human brain structure and functioning, especially one example of this concept – neuroplasticity – automatic adaptation of ANN topology to problem domain.</p>


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