close
Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2014 Jan 8;81(1):35-48.
doi: 10.1016/j.neuron.2013.12.022.

The metastable brain

Emmanuelle Tognoli  1 , J A Scott Kelso  2
Affiliations
Review

The metastable brain

Emmanuelle Tognoli et al. Neuron. .

Abstract

Neural ensembles oscillate across a broad range of frequencies and are transiently coupled or "bound" together when people attend to a stimulus, perceive, think, and act. This is a dynamic, self-assembling process, with parts of the brain engaging and disengaging in time. But how is it done? The theory of Coordination Dynamics proposes a mechanism called metastability, a subtle blend of integration and segregation. Tendencies for brain regions to express their individual autonomy and specialized functions (segregation, modularity) coexist with tendencies to couple and coordinate globally for multiple functions (integration). Although metastability has garnered increasing attention, it has yet to be demonstrated and treated within a fully spatiotemporal perspective. Here, we illustrate metastability in continuous neural and behavioral recordings, and we discuss theory and experiments at multiple scales, suggesting that metastable dynamics underlie the real-time coordination necessary for the brain's dynamic cognitive, behavioral, and social functions.

PubMed Disclaimer

Conflict of interest statement

The authors do not have any financial conflict of interest that might be construed to influence the results or interpretation of the present manuscript.

Figures

Figure 1
Figure 1. Patterns of coordination transcend multiple levels
Coordination dynamics is shown in models (A–C), behavioral data (D–F), and neurophysiological data (G–L). Plots show the coordination variable phi as a function of time. The left column includes samples of relative phase observed during phase-locked coordination (note establishment of states, revealed by persistent horizontal trajectories). Right column shows uncoupled behaviors (note the constant change of the relative phase, called wrapping). Center column shows metastability in which the relative phase exhibits characteristic dwell and escape tendencies, manifested in the alternating mixture of quasi stable and wrapping epochs. See details in text.
Figure 2
Figure 2. Coexisting phase synchrony and metastability
In A, a “chimera” regime is shown, with time on the horizontal axis (arbitrary units) and unwrapped phase on the vertical axis. Having switched to a problem with N 2 elements, we now represent the oscillators’ individual phase (N trajectories) rather than the relative phase (which would suffer a combinatorial explosion with N! trajectories). Furthermore, we unwrap the phase trajectories to avoid the graphical confusion that would arise from wrapped phase intersections. In such graphs of individual phases, integrative tendencies are discovered when trajectories run parallel for a given length of time; trajectories that ascend with different slopes reveal segregation. The time series depict dynamics of oscillators governed by equation 2 above. After an initial transient, the group of oscillators remains perpetually in synchrony (lower box annotated “stable” that stacks the joint phase-trajectory of one third of the oscillators). An “incoherent” group coexists (upper box). Its dynamics consists of a series of escape (segregative tendencies) interspersed with periods of dwells (integrative tendencies), that are typical of metastability. Note undulations in the phase dynamics of the stable components. This undulation both depends on and affects the behavior of the “escapers”, determining their velocity and escape probability in space and time (not shown, see Tognoli and Kelso, 2013). B shows a conceptual ‘big picture’ illustration of the parameter regimes of coordination dynamics - observed for components ranging from similar to different, and coupled with varying strength and heterogeneity. Strong and symmetrical coupling in similar components gives rise to stable behavior, whereas weaker coupling, and/or lesser symmetry in the components and their coupling gives rise to metastability. A hybrid stable~metastable regime exists at the fringe between the two, as exemplified in A.
Figure 3
Figure 3. A behavioral “chimera”
Shown is the relative phase among three pairs of components, left and right index fingers and a periodically flashing light that served as a pacing stimulus. Left and right fingers sustained a state of phase locking (persistently horizontal relative phase trajectory, in green), while at the same time the relative phases between each finger and the pacing stimulus alternated between dwells and escapes, in a manner typical of metastability (pink and blue trajectories).
Figure 4
Figure 4. Dynamic coordination of eight neural ensembles observed in a momentary episode of waking brain EEG activity
(A) scalp topography (projected on x-y axes) and center frequency (z-axis) of each ensemble. (B) unwrapped phase trajectories of each ensemble. Note similarities with Figure 2A. (C) ensemble oscillations in the time domain using adapted bandpass filters. Two organized groups are simultaneously present, one involving three ensembles in the alpha band (identified with numbers 1,2,3 throughout the figure); and the other involving two other ensembles in the gamma band (7,8).
Figure 5
Figure 5. Narrowing the focus of coordination dynamics across scales of observation
(A) illustrates three levels of recording of oscillatory activity: the hypothetical recording of individual neurons (left), local population recording of multiple neurons, for instance as Local Field Potentials (LFP) or intracranial EEG (iEEG)(center) and the global activity captured for instance with high density magnetic (MEG) or electric (EEG) sensor arrays (right). At each upper spatial scale, only the orderly most aspects of neural organization from the lower scale are observable. An example is outlined in figure 5B: when patterns have misaligned phase relationships (left columns), their population signal cancels (middle column) and disappears from the upper scales. The result resembles a state transition regime, although it is more plausible that a single spatiotemporally metastable regime without state transitions spans the entire episode.
See this image and copyright information in PMC

References

    1. Abeles M, Bergman H, Gat I, Meilijson I, Seidemann E, Tishby N, Vaadia E. Cortical activity flips among quasi-stationary states. Proc Natl Acad Sci U S A. 1995;92(19):8616–8620. - PMC - PubMed
    1. Abrams DM, Strogatz SH. Chimera states in rings of nonlocally coupled oscillators. Int J Bifurcat Chaos. 2006;16:21–37.
    1. Akil H, Martone ME, Van Essen DC. Challenges and opportunities in mining Neuroscience data. Science. 2011;331(6018):708–712. - PMC - PubMed
    1. Alba A, Marroquín JL, Arce-Santana E, Harmony T. Classification and interactive segmentation of EEG synchrony patterns. Pattern Recognit. 2010;43(2):530–544.
    1. Allen PG, Collins FS. Toward the final frontier: the human brain. Wall St J (East Ed) 2013 Apr 8; 2013.

Publication types

LinkOut - more resources