On Analysis and Evaluation of Early Math Giftedness Prediction, Regarding Children’s Individual Differences, and Mind Brain Education Science (Neural Networks’ Modeling Approach)

2020 ◽  
Vol 11 (1) ◽  
pp. 295-334
Author(s):  
حسن محمد حسن
Keyword(s):  
Neural Networks ◽  
Individual Differences ◽  
Analysis And Evaluation ◽  
Modeling Approach ◽  
Education Science

scholarly journals Opinion on monoaminergic contributions to traits and temperament

2018 ◽  
Vol 373 (1744) ◽  
pp. 20170153 ◽  
Author(s):  
T. W. Robbins
Keyword(s):  
Neural Networks ◽  
Individual Differences ◽  
Social Functioning ◽  
Personality Factors ◽  
Monoamine Neurotransmitters ◽  
Neural Basis ◽  
Theme Issue ◽  
Experimental Animals ◽  
Neuroscience Research ◽  
Definition Of

This article critically reviews evidence relating temperamental traits and personality factors to the monoamine neurotransmitters, especially dopamine and serotonin. The genetic evidence is not yet considered to be conclusive and it is argued that basic neuroscience research on the neural basis of behaviour in experimental animals should be taken more into account. While questionnaire and lexical methodology including the ‘Five Factor’ theory has been informative (mostly for the traits relevant to social functioning, i.e. personality), biologically oriented approaches should be employed with more objective, theoretically grounded measures of cognition and behaviour, combined with neuroimaging and psychopharmacology, where appropriate. This strategy will enable specific functions of monoamines and other neuromodulators such as acetylcholine and neuropeptides (such as orexin) to be defined with respect to their roles in modulating activity in specific neural networks—leading to a more realistic definition of their interactive roles in complex, biologically based traits (i.e. temperament). This article is part of the theme issue ‘Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences’.

A Wearable Pointing Device Using EMG Signals

2005 ◽  
Vol 17 (2) ◽  
pp. 173-180 ◽  
Author(s):  
Hirotaka Ogino ◽  
◽  
Jun Arita ◽  
Toshio Tsuji
Keyword(s):  
Neural Networks ◽  
Individual Differences ◽  
Experimental Results ◽  
Wearable Computer ◽  
Pointing Device

We propose a wearable pointing device using EMG signals. By using neural networks, the system adapts to variations in EMG signals caused by individual differences of muscular features and minor shifts in electrode sites. Experimental results show that the system, which frees the operator from having to be in front of a computer, is effective as a pointing device for a wearable computer.

Excess of individual variability of priors prevents successful development of general models

2018 ◽  
Vol 41 ◽  
Author(s):  
Talis Bachmann
Keyword(s):  
Individual Differences ◽  
Individual Variability ◽  
Successful Development ◽  
Perceptual Judgments ◽  
Modeling Approach

AbstractPerceptual judgments are influenced by a multitude of factors in addition to the perceptual input. Particularly, the widely varying individual neurobiological endophenotypes and individual differences in the propensity for expectation-based illusory percepts make it unlikely that optimality is possible to define and defend by the type of abstract modeling approach criticized by Rahnev & Denison (R&D).

Neural Networks Reflecting Individual Differences in Intertemporal Decision Making

NeuroImage ◽  
2009 ◽  
Vol 47 ◽  
pp. S117
Author(s):  
LJ Xu ◽  
ZY Liang ◽  
K Wang ◽  
S Li ◽  
TZ Jiang
Keyword(s):  
Neural Networks ◽  
Decision Making ◽  
Individual Differences
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