Nature's Engineering

One criticism of many synchrony- or polychrony-based hypotheses of neural computation is that nature's process of invention is too haphazard to utilize such "engineered" or "engineering"-like solutions. The other major criticism is that the brain is too noisy, and neurons are too sloppy, to achieve such temporal precision (but see this post for evidence that by increasing the diversity of forces acting on an interconnected system of oscillators, the likelihood that synchrony will be observed also increases). Both of these criticisms require any synchrony- or polychrony-based hypothesis to demonstrate how such phenomena might naturally emerge from a biologically plausible and parsimonious architecture. And yet, discoveries like this one reported in a 2003 issue of Proceedings of National Academy of Sciences, show just how advanced nature's "engineering" can be.

In this article, Rizzuto et al. present evidence that during a simple recognition memory task (in which participants had to determine whether a probe stimulus matched one of four previously presented stimuli) theta-clocked oscillations may actually reset upon the presentation of the probe. In other words, before probe presentation, oscillations are out of phase with respect to one another, and therefore the total average power in that frequency band is low. After item presentation, however, all of the electromagnetic waves appear to spontaneously synchronize by resetting their phases at that point (or alternately, by undergoing rapid phase precession).

Further tests showed that prior to item presentation, the distribution of phases was statistically no different from that expected in a uniform distribution, and that after item presentation phases were not uniformly distributed (p<.0001). The authors also explore the possibility that the appearance of phase locking is actually an artifact of simultaneous burst firing, or "transient increases in power," by investigating the total power in each band both before and after item presentation. They found that band power actually decreased significantly after probe presentation in the 7-16 Hz band, which is inconsistent with the idea that transient power increases are giving rise to the appearance of phase-locking. (Aside: this result is reminiscent of findings described previously, in which gamma-band power was seen to be strongest during periods of asynchrony)

Electrodes that showed phase reset to probes were placed in inferior temporal, bilateral occipital, and right parietal regions. Other electrodes showed phase rest to other stimuli, such as the list items (right posterior temporal lobe), and the orienting stimulus (right mesial subtemporal regions). Frontal, prefrontal, and suborbital frontal regions did not show the resetting phenomenon.

As the authors point out, phase resetting may be important for "setting the stage" for other forms of synchrony to emerge, such as gamma- and beta-band oscillations, which have been shown to correlate with successful memory encoding and visual item maintenance, respectively (Fell et al., 2001; Tallon-Baudry, 2001). Jensen and Lisman (1998) have even implemented a computational model in which phase reset (4-12 Hz) initiates serial scanning, which is consistent with Rizzuto et al.'s finding of phase reset on probe presentation.

These results - in which some neural mechanism appears capable of abruptly resetting the phase of multi-band oscillations during item presentation - share striking similarities with phenomena covered in previous posts. For example, results from Nakatani et al.'s 2005 Journal of Cognitive Neuroscience paper (summarized here) can be explained in terms of a slow oscillation (2-3 Hz) operating within a much faster rhythm (38-43 Hz), suggesting that the slower rhythm might be responsible for triggering neural oscillations in response to events in the external world. In other words, slow oscillations may become phase locked with external stimuli, which allows peaks in attentional dynamics (such as capacity or switching) to coincide with the time course of environmental changes.


Fell, J., Klaver, P., Lehnertz, K., Grunwald, T., Schaller, C., Elger, C. E. & Fernandez, G. (2001) Nat. Neurosci. 4, 1259–1264

Jensen, O. & Lisman, J. E. (1998) An oscillatory short-term memory buffer model can account for data on the Sternberg Task. J. Neurosci. 18, 10688–10699.

Tallon-Baudry, C., Bertrand, O. & Fischer, C. (2001) Hebbian reverberating oscillatory synchrony during memory rehearsal in the human brain. J. Neurosci. 21, RC177.

Related Posts:
Entangled Oscillations
Models of Active Maintenance as Oscillation
Chaos, Order, and Coupled Oscillators
Binding through Synchrony: Proof from Developmental Robotics
Sequential Order in Precise Phase Timing
Synchrony and "Perception's Shadow"


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