Emergence of Persistent Networks in Long-Term Intracranial EEG Recordings

被引:88
作者
Kramer, Mark A. [1 ]
Eden, Uri T. [1 ]
Lepage, Kyle Q. [1 ]
Kolaczyk, Eric D. [1 ]
Bianchi, Matt T. [2 ,3 ]
Cash, Sydney S. [2 ,3 ]
机构
[1] Boston Univ, Dept Math & Stat, Boston, MA 02215 USA
[2] Harvard Univ, Sch Med, Boston, MA 02115 USA
[3] Massachusetts Gen Hosp, Dept Neurol, Boston, MA 02114 USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
GRAPH-THEORETICAL ANALYSIS; STATE FUNCTIONAL CONNECTIVITY; SMALL-WORLD; DEFAULT MODE; HUMAN BRAIN; MEASURING SYNCHRONIZATION; GAMMA OSCILLATIONS; COMPLEX NETWORKS; RESTING BRAIN; CORTEX;
D O I
10.1523/JNEUROSCI.2287-11.2011
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Over the past two decades, the increased ability to analyze network relationships among neural structures has provided novel insights into brain function. Most network approaches, however, focus on static representations of the brain's physical or statistical connectivity. Few studies have examined how brain functional networks evolve spontaneously over long epochs of continuous time. To address this, we examine functional connectivity networks deduced from continuous long-term electrocorticogram recordings. For a population of six human patients, we identify a persistent pattern of connections that form a frequency-band-dependent network template, and a set of core connections that appear frequently and together. These structures are robust, emerging from brief time intervals (similar to 100 s) regardless of cognitive state. These results suggest that a metastable, frequency-band-dependent scaffold of brain connectivity exists from which transient activity emerges and recedes.
引用
收藏
页码:15757 / 15767
页数:11
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