Plasticity of brain wave network interactions and evolution across physiologic states.

Kang K L Liu,Rosario N Mantegna,Ronny P Bartsch,Aijing Lin,Plamen Ch Ivanov

doi:10.3389/fncir.2015.00062

Abstract

Neural plasticity transcends a range of spatio-temporal scales and serves as the basis of various brain activities and physiologic functions. At the microscopic level, it enables the emergence of brain waves with complex temporal dynamics. At the macroscopic level, presence and dominance of specific brain waves is associated with important brain functions. The role of neural plasticity at different levels in generating distinct brain rhythms and how brain rhythms communicate with each other across brain areas to generate physiologic states and functions remains not understood. Here we perform an empirical exploration of neural plasticity at the level of brain wave network interactions representing dynamical communications within and between different brain areas in the frequency domain. We introduce the concept of time delay stability (TDS) to quantify coordinated bursts in the activity of brain waves, and we employ a system-wide Network Physiology integrative approach to probe the network of coordinated brain wave activations and its evolution across physiologic states. We find an association between network structure and physiologic states. We uncover a hierarchical reorganization in the brain wave networks in response to changes in physiologic state, indicating new aspects of neural plasticity at the integrated level. Globally, we find that the entire brain network undergoes a pronounced transition from low connectivity in Deep Sleep and REM to high connectivity in Light Sleep and Wake. In contrast, we find that locally, different brain areas exhibit different network dynamics of brain wave interactions to achieve differentiation in function during different sleep stages. Moreover, our analyses indicate that plasticity also emerges in frequency-specific networks, which represent interactions across brain locations mediated through a specific frequency band. Comparing frequency-specific networks within the same physiologic state we find very different degree of network connectivity and link strength, while at the same time each frequency-specific network is characterized by a different signature pattern of sleep-stage stratification, reflecting a remarkable flexibility in response to change in physiologic state. These new aspects of neural plasticity demonstrate that in addition to dominant brain waves, the network of brain wave interactions is a previously unrecognized hallmark of physiologic state and function.

Highlights

Physiological systems and organisms exhibit complex dynamics that continuously change with transitions across physiologic states and conditions by adapting neuronal regulatory mechanisms to optimize function and adequately respond to internal and external stimuli (Ivanov et al, 1999; Kantelhardt et al, 2002; Karasik et al, 2002; Ivanov et al, 2007; Schmitt et al, 2009; Schumann et al, 2010; Bartsch et al, 2012)
The Network Physiology approach we present here fills in this gap through investigations of the horizontal integration among brain waves with different physiologic function, and by probing how physiologic states modulate the network of brain wave interactions across physiologically-relevant frequency bands and brain areas
We build a network of brain wave interactions, where network nodes represent diverse brain waves at different brain locations and network links represent the strength of time delay stability (TDS) coupling between brain waves across the entire brain

Summary

Introduction

Physiological systems and organisms exhibit complex dynamics that continuously change with transitions across physiologic states and conditions by adapting neuronal regulatory mechanisms to optimize function and adequately respond to internal and external stimuli (Ivanov et al, 1999; Kantelhardt et al, 2002; Karasik et al, 2002; Ivanov et al, 2007; Schmitt et al, 2009; Schumann et al, 2010; Bartsch et al, 2012). Neural plasticity occurs at multiple levels of organization and over a broad range of time scales (Destexhe and Marder, 2004). The ability of neurons to react to different inputs and in response to generate various output dynamics serves as a fundamental building block for a broad range of brain functions (Tononi and Cirelli, 2014). Changes in the intrinsic firing properties of individual neurons (Marder et al, 1996) as well as modulation of synaptic strength (Kandel, 2001) play important role in the mechanisms underlying neuronal circuit plasticity (Abeles, 1991; Katz and Frost, 1996; Engel et al, 2001), which in turn affects the integrative properties of neurons leading to transitions in large network behavior. As a direct consequence of plasticity at the neuronal, synaptic, and circuitry level a variety of brain waves emerge with different dominant rhythms (Steriade et al, 1993; Traub et al, 2001; Steriade and Timofeev, 2003; Hill and Tononi, 2005; Millman et al, 2010; Olcese et al, 2010)

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