scholarly journals A Review on the Occipital Area Morphology in Nyctereutes Procyonoides cancrivora--Evidence for Developmental Instability?

2016 ◽  
Author(s):  
Samuel O.M ◽  
Olopade J.O
Keyword(s):  
Developmental Instability ◽  
Nyctereutes Procyonoides ◽  
Occipital Area

scholarly journals Fluctuating Asymmetry and Developmental Instability, a Guide to Best Practice

Symmetry ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 9
Author(s):  
John H. Graham
Keyword(s):  
Measurement Error ◽  
Best Practices ◽  
Environmental Stress ◽  
Fluctuating Asymmetry ◽  
Best Practice ◽  
Developmental Instability ◽  
The Past ◽  
Size Scaling ◽  
Research Designs

Best practices in studies of developmental instability, as measured by fluctuating asymmetry, have developed over the past 60 years. Unfortunately, they are haphazardly applied in many of the papers submitted for review. Most often, research designs suffer from lack of randomization, inadequate replication, poor attention to size scaling, lack of attention to measurement error, and unrecognized mixtures of additive and multiplicative errors. Here, I summarize a set of best practices, especially in studies that examine the effects of environmental stress on fluctuating asymmetry.

scholarly journals Nature, Nurture, and Noise: Developmental Instability, Fluctuating Asymmetry, and the Causes of Phenotypic Variation

Symmetry ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1204
Author(s):  
John H. Graham
Keyword(s):  
Fluctuating Asymmetry ◽  
Phenotypic Variation ◽  
Deterministic Chaos ◽  
Monozygotic Twins ◽  
Developmental Instability ◽  
Nonlinear Feedback ◽  
Developmental Variation ◽  
Sewall Wright ◽  
Developmental Noise ◽  
And Behavior

Phenotypic variation arises from genetic and environmental variation, as well as random aspects of development. The genetic (nature) and environmental (nurture) components of this variation have been appreciated since at least 1900. The random developmental component (noise) has taken longer for quantitative geneticists to appreciate. Here, I sketch the historical development of the concepts of random developmental noise and developmental instability, and its quantification via fluctuating asymmetry. The unsung pioneers in this story are Hugo DeVries (fluctuating variation, 1909), C. H. Danforth (random variation between monozygotic twins, 1919), and Sewall Wright (random developmental variation in piebald guinea pigs, 1920). The first pioneering study of fluctuating asymmetry, by Sumner and Huestis in 1921, is seldom mentioned, possibly because it failed to connect the observed random asymmetry with random developmental variation. This early work was then synthesized by Boris Astaurov in 1930 and Wilhelm Ludwig in 1932, and then popularized by Drosophila geneticists beginning with Kenneth Mather in 1953. Population phenogeneticists are still trying to understand the origins and behavior of random developmental variation. Some of the developmental noise represents true stochastic behavior of molecules and cells, while some represents deterministic chaos, nonlinear feedback, and symmetry breaking.

scholarly journals CORRELATING DESIGN PERFORMANCE TO EEG ACTIVATION: EARLY EVIDENCE FROM EXPERIMENTAL DATA

2021 ◽  
Vol 1 ◽  
pp. 771-780
Author(s):  
Shumin Li ◽  
Niccolò Becattini ◽  
Gaetano Cascini
Keyword(s):  
Idea Generation ◽  
Occipital Area ◽  
Experimental Protocol ◽  
Brain Response ◽  
Design Task ◽  
Early Evidence ◽  
Eeg Data ◽  
Eeg Activation ◽  
Level Design ◽  
Eeg Alpha

AbstractThis paper presents an EEG (Electroencephalography) study that explores correlations between the neurophysiological activations, the nature of the design task and its outputs. We propose an experimental protocol that covers several design-related tasks: including fundamental activities (e.g. idea generation and problem-solving) as well as more comprehensive task requiring the complex higher-level reasoning of designing. We clustered the collected data according to the characteristics of the design outcome and measured EEG alpha band activation during elementary and higher-level design task, whereas just the former yielded statistically significant different behaviour in the left frontal and occipital area. We also found a significant correlation between the ratings for elementary sketching task outcomes and EEG activation at the higher-level design task. These results suggested that EEG activation enables distinguishing groups according to their performance only for elementary tasks. However, this also suggests a potential application of EEG data on the elementary tasks to distinguish the designers' brain response during higher-level of design task.

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