Abstract
Slow oscillations in neuronal activity in the human brain are the defining feature of scalp-measured electroencephalography taken under general anesthesia. A theoretical investigation of a model for the human cortex reveals that slow spatiotemporal patterns emerge spontaneously as the result of a chemically modified balancing act between two instabilities in cortical dynamics---one to spatial organizations and the other to temporal bifurcation. Long-range interneuronal communication across the cortex is shown to be crucial to the pattern formation.
Highlights
Over the past two decades, extensive imaging studies using functional magnetic resonance imaging and positron emission tomography (PET) have demonstrated that, during specific cognitive tasks, human subjects exhibit a high degree of spatial organization in neuronal activation [1]
We have suggested previously that the slow beating dynamics (& 0:1 Hz) observed in blood oxygen-level-dependent (BOLD) functional MRI recordings during default network activation [5] arises from a competitive interaction between Turing and Hopf instabilities: The inhibitory diffusion strength D2 mediates pattern formation, and the inhibitory rate constant i mediates network oscillation [29]
We identify the mixed-mode chaotic dynamics as ‘‘anesthetic slow-wave’’ because its time series and spectrum are very similar to the distorted slow-wave sleep patterns seen in general anesthesia
Summary
Over the past two decades, extensive imaging studies using functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) have demonstrated that, during specific cognitive tasks, human subjects exhibit a high degree of spatial organization in neuronal activation [1]. While there is evidence linking imaging patterns retrieved from blood oxygen-level-dependent (BOLD) studies to hard-wired axonal pathways defined by specific anatomic projections [2,3], known connectivities cannot account for many of the correlated BOLD observations [4,5,6]. This absence of a clear mapping between anatomical connectivity and cognitive function. It is our belief that aspects of the observed patterns of neural activation can be generated by intrinsic Turing and Hopf instabilities that emerge spontaneously under physiologically realistic modulation of cortical parameters. We advance the idea that normal brain function requires a delicate balance between these instabilities
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