Alpha/beta power decreases track the fidelity of stimulus-specific information

Abstract

Massed synchronised neuronal firing is detrimental to information processing. When networks of taskirrelevant neurons fire in unison, they mask the signal generated by task-critical neurons. On a macroscopic level, mass synchronisation of these neurons can contribute to the ubiquitous alpha/beta (8-30Hz) oscillations. Reductions in the amplitude of these oscillations, therefore, may reflect a boost in the processing of highfidelity information within the cortex. Here, we test this hypothesis. Twenty-one participants completed an associative memory task while undergoing simultaneous EEG-fMRI recordings. Using representational similarity analysis, we quantified the amount of stimulus-specific information represented within the BOLD signal on every trial. When correlating this metric with concurrently-recorded alpha/beta power, we found a significant negative correlation which indicated that as alpha/beta power decreased, our metric of stimulus-specific information increased. This effect generalised across cognitive tasks, as the negative relationship could be observed during visual perception and episodic memory retrieval. Further analysis revealed that this effect could be better explained by alpha/beta power decreases providing favourable conditions for information processing, rather than directly representing stimulus-specific information. Together, these results indicate that alpha/beta power decreases parametrically track the fidelity of both externally-presented and internallygenerated stimulus-specific information represented within the cortex.

Distinct cortical systems reinstate the content and context of episodic memories

“…Thus, increases in neuronal firing within attributespecific cortical regions would support accurate decoding. At the same time, reduction of oscillations and increased asynchronous activity supports information coding within cortex 65,66 . Changes in the amplitude of narrowband oscillations would therefore contribute to decoding performance, at timescales constrained by the speed of the oscillation.…”

Human motor cortical beta bursts relate to movement planning and response errors

“…Speculatively, if seen as a communication and integrating mechanism, beta bursts may not reflect the specific local computations necessary for movement per se, but represent brief periods of interregional communication [46], which could include functions such as goal formation or post-performance evaluation and integration [10,15,73]. Such a view would be broadly compatible with the idea that strongly correlated neural spiking, as is the case for beta power increases, reduces the capacity for local information processing [84] but could open up channels for longer range communication [85]. Recent evidence suggests that during periods of beta bursting, rapid interregional phase locking occurs, starting just prior to and for the duration of the burst, providing a direct possible mechanism of how such interregional communication could occur [71].…”

Alpha/beta power decreases during episodic memory formation predict the magnitude of alpha/beta power decreases during subsequent retrieval

“…Given that these noise correlations share a strong positive correlation with local field potential (LFP; Cui et al, 2016), one could speculate that the ubiquitous reduction in alpha/beta power that arises during task engagement (e.g., Crone et al, 1998;Krause et al, 1994;Pfurtscheller et al, 1996) may reflect a reduction in underlying noise correlations. In line with this idea, growing evidence suggests that alpha/beta power decreases support the representation of information encoded within, and retrieved from, episodic memories (Griffiths, Mayhew, et al, 2019;Karlsson et al, 2020;Martín-Buro et al, 2020). For example, a simultaneous EEG-fMRI study demonstrated that the magnitude of alpha/beta power decreases directly correlated with the amount of stimulus-specific information represented within the BOLD signal during both perception and episodic memory retrieval (Griffiths, Mayhew, et al, 2019).…”