Emergence of Persistent Networks in Long-Term Intracranial EEG Recordings

Department of Mathematics and Statistics, Boston University, Boston, Massachusetts 02215, USA.
The Journal of Neuroscience : The Official Journal of the Society for Neuroscience (Impact Factor: 6.34). 11/2011; 31(44):15757-67. DOI: 10.1523/JNEUROSCI.2287-11.2011
Source: PubMed


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 (~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.

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Available from: Mark A Kramer, May 01, 2014
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    • "However, it is also fascinating that a system composed of a tremendous number of highly crosslinked dynamical units with continuously changing parameters and external perturbations can also show constant aspects in its evolution (Buckner et al., 2008; Fox et al., 2005; Greicius, 2008; Greicius et al., 2003; Honey et al., 2009; Jann et al., 2010; Nyberg et al., 1996; Raichle and Mintun, 2006; Raichle et al., 2001; Shulman et al., 1997). Analysis of long-term interictal periods of intracranial EEG recordings, for example, indicates the existence of a stationary correlation structure, which remains stable over a period of at least 24 h (Kramer et al., 2011). Stable correlations between blood oxygenation level dependent signals, slow cortical potentials, and band limited power in interictal periods of electrocorticograms of epilepsy patients during sleep and awake states have also been reported (He, 2008). "
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