Genetic links between brain development and brain evolution

2005 ◽  
Vol 6 (7) ◽  
pp. 581-590 ◽  
Author(s):  
Sandra L. Gilbert ◽  
William B. Dobyns ◽  
Bruce T. Lahn
Keyword(s):  
Brain Development ◽  
Brain Evolution

scholarly journals Understanding well–being in the evolutionary context of brain development

2004 ◽  
Vol 359 (1449) ◽  
pp. 1349-1358 ◽  
Author(s):  
Eric B. Keverne
Keyword(s):  
Brain Development ◽  
Positive Emotions ◽  
Brain Evolution ◽  
Well Being ◽  
Regulatory Control ◽  
Brain Maturation ◽  
Association Cortex ◽  
Evolutionary Context ◽  
Emotional Behaviour ◽  
Early Life Events

Much of the work on well–being and positive emotions has tended to focus on the adult, partly because this is when problems are manifest and well–being often becomes an issue by its absence. However, it is pertinent to ask if early life events might engender certain predispositions that have consequences for adult well–being. The human brain undergoes much of its growth and development postnatally until the age of seven and continues to extend its synaptic connections well into the second decade. Indeed, the prefrontal association cortex, areas of the brain concerned with forward planning and regulatory control of emotional behaviour, continue to develop until the age of 20. In this article, I consider the significance of this extended postnatal developmental period for brain maturation and how brain evolution has encompassed certain biological changes and predispositions that, with our modern lifestyle, represent risk factors for well–being. An awareness of these sensitive phases in brain development is important in understanding how we might facilitate secure relationships and high self–esteem in our children. This will provide the firm foundations on which to develop meaningful lifestyles and relationships that are crucial to well–being.

scholarly journals Murine Otx1 and Drosophila otd genes share conserved genetic functions required in invertebrate and vertebrate brain development

Development ◽  
1998 ◽  
Vol 125 (9) ◽  
pp. 1691-1702 ◽  
Author(s):  
D. Acampora ◽  
V. Avantaggiato ◽  
F. Tuorto ◽  
P. Barone ◽  
H. Reichert ◽  
...  
Keyword(s):  
Brain Development ◽  
Expression Patterns ◽  
Brain Evolution ◽  
Mammalian Brain ◽  
Gene Products ◽  
Functional Conservation ◽  
Vertebrate Brain ◽  
Functional Differences ◽  
Mutant Phenotypes ◽  
Insight Into

Despite the obvious differences in anatomy between invertebrate and vertebrate brains, several genes involved in the development of both brain types belong to the same family and share similarities in expression patterns. Drosophila orthodenticle (otd) and murine Otx genes exemplify this, both in terms of expression patterns and mutant phenotypes. In contrast, sequence comparison of OTD and OTX gene products indicates that homology is restricted to the homeodomain suggesting that protein divergence outside the homeodomain might account for functional differences acquired during brain evolution. In order to gain insight into this possibility, we replaced the murine Otx1 gene with a Drosophila otd cDNA. Strikingly, epilepsy and corticogenesis defects due to the absence of Otx1 were fully rescued in homozygous otd mice. A partial rescue was also observed for the impairments of mesencephalon, eye and lachrymal gland. In contrast, defects of the inner ear were not improved suggesting a vertebrate Otx1-specific function involved in morphogenesis of this structure. Furthermore, otd, like Otx1, was able to cooperate genetically with Otx2 in brain patterning, although with reduced efficiency. These data favour an extended functional conservation between Drosophila otd and murine Otx1 genes and support the idea that conserved genetic functions required in mammalian brain development evolved in a primitive ancestor of both flies and mice.

Developmental Swarm Intelligence

2016 ◽  
pp. 349-367
Author(s):  
Yuhui Shi
Keyword(s):  
Brain Development ◽  
Evolutionary Algorithm ◽  
Swarm Intelligence ◽  
Brain Evolution ◽  
Developmental Learning ◽  
Intelligence Algorithm ◽  
Swarm Intelligence Algorithm

In this article, the necessity of having developmental learning embedded in a swarm intelligence algorithm is confirmed by briefly considering brain evolution, brain development, brainstorming process, etc. Several swarm intelligence algorithms are looked at from developmental learning perspective. Finally, a framework of a developmental swarm intelligence algorithm is given to help understand developmental swarm intelligence algorithms, and to guide to design and/or implement any new developmental swarm intelligence algorithm and/or any developmental evolutionary algorithm.

Developmental Swarm Intelligence

2014 ◽  
Vol 5 (1) ◽  
pp. 36-54 ◽  
Author(s):  
Yuhui Shi
Keyword(s):  
Brain Development ◽  
Evolutionary Algorithm ◽  
Swarm Intelligence ◽  
Brain Evolution ◽  
Developmental Learning ◽  
Intelligence Algorithm ◽  
Swarm Intelligence Algorithm

In this paper, the necessity of having developmental learning embedded in a swarm intelligence algorithm is confirmed by briefly considering brain evolution, brain development, brainstorming process, etc. Several swarm intelligence algorithms are looked at from developmental learning perspective. Finally, a framework of a developmental swarm intelligence algorithm is given to help understand developmental swarm intelligence algorithms, and to guide to design and/or implement any new developmental swarm intelligence algorithm and/or any developmental evolutionary algorithm.

Forebrain Architecture and Development in Cyclostomes, with Reference to the Early Morphology and Evolution of the Vertebrate Head

2021 ◽  
pp. 1-13
Author(s):  
Fumiaki Sugahara ◽  
Yasunori Murakami ◽  
Juan Pascual-Anaya ◽  
Shigeru Kuratani
Keyword(s):  
Brain Development ◽  
Brain Evolution ◽  
Ct Scanning ◽  
Craniofacial Morphology ◽  
Last Common Ancestor ◽  
Developmental Studies ◽  
Developmental Mechanism ◽  
Anterior Division ◽  
Head Morphology ◽  
The Brain

The vertebrate head and brain are characterized by highly complex morphological patterns. The forebrain, the most anterior division of the brain, is subdivided into the diencephalon, hypothalamus, and telencephalon from the neuromeric subdivision into prosomeres. Importantly, the telencephalon contains the cerebral cortex, which plays a key role in higher order cognitive functions in humans. To elucidate the evolution of the forebrain regionalization, comparative analyses of the brain development between extant jawed and jawless vertebrates are crucial. Cyclostomes – lampreys and hagfishes – are the only extant jawless vertebrates, and diverged from jawed vertebrates (gnathostomes) over 500 million years ago. Previous developmental studies on the cyclostome brain were conducted mainly in lampreys because hagfish embryos were rarely available. Although still scarce, the recent availability of hagfish embryos has propelled comparative studies of brain development and gene expression. By integrating findings with those of cyclostomes and fossil jawless vertebrates, we can depict the morphology, developmental mechanism, and even the evolutionary path of the brain of the last common ancestor of vertebrates. In this review, we summarize the development of the forebrain in cyclostomes and suggest what evolutionary changes each cyclostome lineage underwent during brain evolution. In addition, together with recent advances in the head morphology in fossil vertebrates revealed by CT scanning technology, we discuss how the evolution of craniofacial morphology and the changes of the developmental mechanism of the forebrain towards crown gnathostomes are causally related.

Regressive Events in Brain Development and Scenarios for Vertebrate Brain Evolution

1987 ◽  
Vol 30 (1-2) ◽  
pp. 102-117 ◽  
Author(s):  
Barbara L. Finlay ◽  
Kenneth C. Wikler ◽  
Dale R. Sengelaub
Keyword(s):  
Brain Development ◽  
Brain Evolution ◽  
Vertebrate Brain ◽  
Regressive Events

Regressive Events in Brain Development and Scenarios for Vertebrate Brain Evolution (Part 2 of 2)

1987 ◽  
Vol 30 (1-2) ◽  
pp. 109-117
Author(s):  
Barbara L. Finlay ◽  
Kenneth C. Wikler ◽  
Dale R. Sengelaub
Keyword(s):  
Brain Development ◽  
Brain Evolution ◽  
Vertebrate Brain ◽  
Regressive Events

scholarly journals Regulation of Neural Stem Cell Competency and Commitment during Indirect Neurogenesis

2021 ◽  
Vol 22 (23) ◽  
pp. 12871
Author(s):  
Arjun Rajan ◽  
Cyrina M. Ostgaard ◽  
Cheng-Yu Lee
Keyword(s):  
Stem Cell ◽  
Brain Development ◽  
Neural Stem Cell ◽  
Brain Evolution ◽  
Fruit Fly ◽  
Larval Brain ◽  
Intermediate Progenitors ◽  
Asymmetric Divisions ◽  
Stem Cell Division

Indirect neurogenesis, during which neural stem cells generate neurons through intermediate progenitors, drives the evolution of lissencephalic brains to gyrencephalic brains. The mechanisms that specify intermediate progenitor identity and that regulate stem cell competency to generate intermediate progenitors remain poorly understood despite their roles in indirect neurogenesis. Well-characterized lineage hierarchy and available powerful genetic tools for manipulating gene functions make fruit fly neural stem cell (neuroblast) lineages an excellent in vivo paradigm for investigating the mechanisms that regulate neurogenesis. Type II neuroblasts in fly larval brains repeatedly undergo asymmetric divisions to generate intermediate neural progenitors (INPs) that undergo limited proliferation to increase the number of neurons generated per stem cell division. Here, we review key regulatory genes and the mechanisms by which they promote the specification and generation of INPs, safeguarding the indirect generation of neurons during fly larval brain neurogenesis. Homologs of these regulators of INPs have been shown to play important roles in regulating brain development in vertebrates. Insight into the precise regulation of intermediate progenitors will likely improve our understanding of the control of indirect neurogenesis during brain development and brain evolution.

Unified Swarm Intelligence Algorithms

2018 ◽  
pp. 1-26 ◽  
Author(s):  
Yuhui Shi
Keyword(s):  
Brain Development ◽  
Evolutionary Algorithm ◽  
Swarm Intelligence ◽  
Brain Evolution ◽  
Learning Stage ◽  
Developmental Learning ◽  
Intelligence Algorithm ◽  
Swarm Intelligence Algorithm

In this chapter, the necessity of having developmental learning embedded in a swarm intelligence algorithm is confirmed by briefly considering brain evolution, brain development, brainstorming process, etc. Several swarm intelligence algorithms are looked at from a developmental learning perspective. A framework of a developmental swarm intelligence algorithm, which contains capacity developing stage and capability learning stage, is further given to help understand developmental swarm intelligence (DSI) algorithms, and to guide to design and/or implement any new developmental swarm intelligence algorithm and/or any developmental evolutionary algorithm. Following DSI, innovation is discussed and an innovation-inspired optimization (IO) algorithm is designed and developed. Finally, by combing the DSI and IO algorithm together, a unified swarm intelligence algorithm is proposed, which contains capacity developing stage and capability learning stage and with three search operators in its capability learning stage to mimic the three levels of innovations.

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