Using big data to map the network organization of the brain

被引：4

作者：

Swain, James E. ^{[1
,2
,4
]}

Sripada, Chandra ^{[1
,3
]}

Swain, John D. ^{[5
]}

机构：

[1] Univ Michigan, Sch Med, Dept Psychiat, Ann Arbor, MI 48109 USA

[2] Univ Michigan, Dept Psychol, Ann Arbor, MI 48105 USA

[3] Univ Michigan, Dept Philosophy, Ann Arbor, MI 48105 USA

[4] Yale Univ, Sch Med, Child Study Ctr, New Haven, CT 06520 USA

[5] Northeastern Univ, Dept Phys, Boston, MA 02115 USA

来源：

BEHAVIORAL AND BRAIN SCIENCES | 2014年 / 37卷 / 01期

关键词：

D O I：

10.1017/S0140525X13001908

中图分类号：

B84 [心理学];

学科分类号：

04 ; 0402 ;

摘要：

The past few years have shown a major rise in network analysis of "big data" sets in the social sciences, revealing non-obvious patterns of organization and dynamic principles. We speculate that the dependency dimension - individuality versus sociality - might offer important insights into the dynamics of neurons and neuronal ensembles. Connectomic neural analyses, informed by social network theory, may be helpful in understanding underlying fundamental principles of brain organization.

引用

页码：101 / 102

页数：2

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