Trends in Cognitive Sciences
ReviewScale-free brain activity: past, present, and future
Introduction
A student entering neuroscience today might learn about the irregular, Poisson-like firing in cortical pyramidal neurons on the one hand, and the plethora of brain oscillations on the other hand. Both are well-established neuroscience phenomena: the former from single- or multiunit recordings of neuronal spiking, the latter from recordings of brain electrical field potentials, such as local field potentials (LFP), EEG, and MEG. Why is it that one modality has emphasized irregular patterns of neural activity, whereas the other has emphasized oscillatory patterns? In fact, regular, rhythmic neuronal firing patterns do exist in cortical excitatory neurons; they are just less common 1, 2, 3 (Figure 1A). Irregular, arrhythmic (see Glossary) field potential activity patterns also exist (Figure 1B) and account for the majority of the signal power recorded in LFP, EEG, and/or MEG experiments (Figure 1C), but are less studied than brain oscillations. In this review, I focus on what we currently know about this prevalent, arrhythmic component of brain field potentials, and identify several urgent questions in this research field.
Section snippets
Brain oscillations versus scale-free brain activity
Brain oscillations are recurring patterns of brain activity that follow a particular temporal beat. For example, the first discovered EEG rhythm, the occipital alpha wave, proceeds at approximately 10 cycles per second [4]. Thus, brain oscillations are most easily identified in the frequency domain, because their power spectra contain peaks at the corresponding frequency ranges (arrows in Figure 1C). There are several brain oscillations at different frequency ranges, each with their own
Scale-free brain activity is not unstructured noise
1/f-type temporal dynamics are prevalent not only in the nervous system, but also in nature at large 36, 37. The ubiquity of scale-free dynamics in a variety of systems was often taken as evidence that these dynamics lack functional specificity, as exemplified by the colloquial name ‘1/f noise.’ To a large extent, the historical neglect of scale-free brain activity is due to this deflationary interpretation of scale-free dynamics. However, it is important to keep in mind that the power spectrum
Beyond nested frequencies
Nonetheless, what do these nested-frequency patterns in scale-free dynamics mean? Nested-frequency analysis necessitates filtering the broadband signal in different frequency ranges and extracting the phase and power of a lower- and a higher- frequency band, respectively. Whereas it is straightforward to characterize the phase and power corresponding to rhythmic brain oscillations, the interpretation of phase and power extracted from filtered arrhythmic signals requires more caution. Although
Functional significance of scale-free brain activity
Research on the functional roles of scale-free brain activity is just beginning. Nonetheless, there are several tantalizing lines of evidence suggesting that it is intimately related to brain functioning.
First, the broadband (approximately 5∼200 Hz) power of LFPs has been shown to correlate tightly with population neuronal firing rates in both human and macaque 14, 46. Ray and Maunsell [46] presented an impressive dissociation between scale-free brain activity and brain oscillation in the same
Generative mechanisms of scale-free brain activity
What are the generative mechanisms of scale-free brain activity? In this section, I first focus on existing computational modeling studies on the power spectral shape of invasively recorded LFP and ECoG signals, and then describe the discrepancy of the power-law exponent observed across modalities and the intriguing questions posed by these findings.
Relation between broadband activity, amplitude fluctuations of brain oscillations, and neuronal avalanches
In this review, I focused on scale-free dynamics in the raw fluctuations of broadband (from <0.01 Hz to ∼500 Hz) electrical and magnetic signals from the brain, as well as the low-frequency (<0.5 Hz) activity recorded in fMRI. As mentioned above, the amplitude fluctuations of narrow-band brain oscillations also exhibit scale-free dynamics [20]; moreover, a recent burgeoning literature has demonstrated the functional 26, 27, 59, developmental [29], and clinical [34] relevance of this phenomenon.
Acknowledgments
This work was supported by the Intramural Research program of the NIH/NINDS. I thank Xiao-Jing Wang and Rishidev Chaudhuri for discussions; Qi Li and Zachary Hill for collecting resting-state MEG and EEG data for estimating the power-law exponent; and Brian Maniscalco and three anonymous reviewers for helpful feedback on previous drafts.
Glossary
- Arrhythmic
- without a predominant temporal frequency, often used interchangeably with ‘aperiodic’ and ‘irregular’.
- Brain oscillations
- brain activity patterns that recur with a particular temporal frequency.
- Exponentially decaying function
- , where X is a time-varying function and λ is the decay rate. It is called ‘exponentially decaying’ because the solution to this function is: X(t) = X0e−λt. Convolution of two exponential functions can be written as: and . In the context
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