Computational Developmental Neuroscience: Capturing Developmental Trajectories From Genes to Cognition

被引:3
|
作者
Thivierge, Jean-Philippe [1 ]
机构
[1] Indiana Univ, Dept Psychol & Brain Sci, Bloomington, IN 47405 USA
基金
加拿大自然科学与工程研究理事会;
关键词
Axonal growth; computational model; development; intrinsic activity; synaptic plasticity; EXPERIENCE-DEPENDENT PLASTICITY; RETINOTOPIC MAP REFINEMENT; SPONTANEOUS RETINAL WAVES; MOLECULAR GRADIENTS; FUNCTIONAL CONNECTIVITY; CORRELATED ACTIVITY; CORTICAL NETWORKS; MODEL; SYNAPSES; MECHANISMS;
D O I
10.1109/TAMD.2010.2041776
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Over the course of development, the central nervous system grows into a complex set of structures that ultimately controls our experiences and interactions with the world. To understand brain development, researchers must disentangle the contributions of genes, neural activity, synaptic plasticity, and intrinsic noise in guiding the growth of axons between brain regions. Here, we examine how computer simulations can shed light on neural development, making headway towards systems that self-organize into fully autonomous models of the brain. We argue that these simulations should focus on the "open-ended" nature of development, rather than a set of deterministic outcomes.
引用
收藏
页码:51 / 58
页数:8
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