Neural Correlates of Realisation of Satisfaction in a Successful Search Process

2021 ◽  
Vol 58 (1) ◽  
pp. 282-291
Author(s):  
Sakrapee Paisalnan ◽  
Yashar Moshfeghi ◽  
Frank Pollick
Keyword(s):  
Neural Correlates ◽  
Search Process ◽  
Successful Search

scholarly journals SEARCHING FOR TARGETS ON A MODEL DNA: EFFECTS OF INTER-SEGMENT HOPPING, DETACHMENT, AND RE-ATTACHMENT

2009 ◽  
Vol 20 (06) ◽  
pp. 817-830
Author(s):  
DEBANJAN CHOWDHURY
Keyword(s):  
Binding Site ◽  
Specific Binding ◽  
Specific Site ◽  
Search Process ◽  
Biological Processes ◽  
Base Pairs ◽  
Successful Search ◽  
Single Protein ◽  
Relevant Quantity

For most of the important processes in DNA metabolism, a protein has to reach a specific binding site on the DNA. The specific binding site may consist of just a few base-pairs while the DNA is usually several millions of base-pairs long. How does the protein search for the target site? What is the most efficient mechanism for a successful search? Motivated by these fundamental questions on intracellular biological processes, we have developed a model for searching a specific site on a model DNA by a single protein. We have made a comparative quantitative study on the efficiencies of sliding, inter-segmental hoppings and detachment/re-attachments of the particle during its search for the specific site on the DNA. We also introduce some new quantitative measures of efficiency of a search process by defining a relevant quantity, which can be measured in in-vitro experiments.

scholarly journals Handling Optimization Problem, and the Scope of Varied Artificial Bee Colony (ABC) Algorithms: A Contemporary

2019 ◽  
Vol 8 (6S4) ◽  
pp. 607-611
Keyword(s):  
Honey Bees ◽  
Optimization Problem ◽  
Artificial Bee Colony ◽  
Research Community ◽  
Food Sources ◽  
Search Process ◽  
Abc Algorithm ◽  
Success Stories ◽  
Bee Colony ◽  
Successful Search

One of the most successful search algorithms of the last decade is Artificial Bee Colony (ABC) algorithm. It was first coined by Dervis Karaboga, 2005. Since then a group of variants of the algorithm have been anticipated to find solutions for the problems of optimization. The motivation for the algorithm is the search process of honey bees for food sources. The present paper aimed to bring out the evolutionary developments of the algorithm that cover numerous versions of the algorithm with the strategic changes to meet the optimization needs of the adopted problem contexts. This survey clearly reviewed the basic types, advancements, application areas, and the relevance of the ABC algorithm addressing various problem contexts. The efforts made by the research community since the last two decades along with the success stories are discussed in detail. The attachment of the optimization process of ABC with data mining is dealt in particular. Finally the opportunities and the scope of the application of the algorithm in large areas of problem domains are highlighted.

scholarly journals Parallel exploration via negatively correlated search

2021 ◽  
Vol 15 (5) ◽  
Author(s):  
Peng Yang ◽  
Qi Yang ◽  
Ke Tang ◽  
Xin Yao
Keyword(s):  
Reinforcement Learning ◽  
Probabilistic Models ◽  
Search Space ◽  
Mathematical Understanding ◽  
Search Process ◽  
High Quality ◽  
Empirical Results ◽  
Successful Search ◽  
Search Processes ◽  
Deep Convolution Network

AbstractEffective exploration is key to a successful search process. The recently proposed negatively correlated search (NCS) tries to achieve this by coordinated parallel exploration, where a set of search processes are driven to be negatively correlated so that different promising areas of the search space can be visited simultaneously. Despite successful applications of NCS, the negatively correlated search behaviors were mostly devised by intuition, while deeper (e.g., mathematical) understanding is missing. In this paper, a more principled NCS, namely NCNES, is presented, showing that the parallel exploration is equivalent to a process of seeking probabilistic models that both lead to solutions of high quality and are distant from previous obtained probabilistic models. Reinforcement learning, for which exploration is of particular importance, are considered for empirical assessment. The proposed NCNES is applied to directly train a deep convolution network with 1.7 million connection weights for playing Atari games. Empirical results show that the significant advantages of NCNES, especially on games with uncertain and delayed rewards, can be highly owed to the effective parallel exploration ability.

Neural correlates of postformal stages of reasoning: Biological determinants of developmental stage.

2016 ◽  
Vol 21 (1) ◽  
pp. 33-43 ◽  
Author(s):  
Sofia Ribeirinho Leite ◽  
Cory David Barker ◽  
Marc G. Lucas
Keyword(s):  
Developmental Stage ◽  
Neural Correlates ◽  
Biological Determinants

In Brief: Study Examines Neural Correlates of Sympathy.

2003 ◽  
Author(s):  
E. Benson
Keyword(s):  
Neural Correlates

Neural Correlates of Early and Later-learned Relational Judgments

2012 ◽  
Author(s):  
Nicole Scott ◽  
Apostolos Georgopoulos ◽  
Maria Sera
Keyword(s):  
Neural Correlates ◽  
Relational Judgments

Neural correlates of executive control training

2011 ◽  
Author(s):  
J. Karbach ◽  
S. Brieber
Keyword(s):  
Executive Control ◽  
Neural Correlates

Neural Correlates in the Processing of Auditory Spatial Cues and Stimuli Direction

2007 ◽  
Author(s):  
Marco Sperduti ◽  
Ralf Veit ◽  
Andrea Caria ◽  
Paolo Belardinelli ◽  
Niels Birbaumer ◽  
...  
Keyword(s):  
Neural Correlates ◽  
Spatial Cues ◽  
Auditory Spatial Cues

Expected Risks and Returns in Children's, Adolescents', and Adults' Dynamic Risky Choice: Behavioral Effects and Neural Correlates

2013 ◽  
Author(s):  
Elke U. Weber ◽  
Anna C. van Duijvenvoorde ◽  
Leah H. Somerville ◽  
Alisa Powers ◽  
Wouter D. Weeda ◽  
...  
Keyword(s):  
Neural Correlates ◽  
Risky Choice ◽  
Behavioral Effects ◽  
Adolescents And Adults

Reappraisal versus distraction: The neural correlates of emotion regulation

2010 ◽  
Author(s):  
Brandy N. Johnson ◽  
Robert L. West
Keyword(s):  
Emotion Regulation ◽  
Neural Correlates
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