Alpha Rhythms Reveal When and Where Item and Associative Memories Are Retrieved

Abstract

Memories for past experiences can range from vague recognition to full-blown recall of associated details. Electroencephalography has shown that recall signals unfold a few hundred milliseconds after simple recognition, but has only provided limited insights into the underlying brain networks. Functional magnetic resonance imaging (fMRI) has revealed a "core recollection network" (CRN) centered on posterior parietal and medial temporal lobe regions, but the temporal dynamics of these regions during retrieval remain largely unknown. Here we used Magnetoencephalography in a memory paradigm assessing correct rejection (CR) of lures, item recognition (IR) and associative recall (AR) in human participants of both sexes. We found that power decreases in the alpha frequency band (10-12 Hz) systematically track different mnemonic outcomes in both time and space: Over left posterior sensors, alpha power decreased in a stepwise fashion from 500 ms onward, first from CR to IR and then from IR to AR. When projecting alpha power into source space, the CRN known from fMRI studies emerged, including posterior parietal cortex (PPC) and hippocampus. While PPC showed a monotonic change across conditions, hippocampal effects were specific to recall. These region-specific effects were corroborated by a separate fMRI dataset. Importantly, alpha power time courses revealed a temporal dissociation between item and associative memory in hippocampus and PPC, with earlier AR effects in hippocampus. Our data thus link engagement of the CRN to the temporal dynamics of episodic memory and highlight the role of alpha rhythms in revealing when and where different types of memories are retrieved.

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

“…This matches numerous previous studies linking alpha/beta power decreases to successful memory retrieval (e.g. Griffiths et al, 2020;Griffiths, Mayhew, et al, 2019;Karlsson et al, 2020;Khader & Rösler, 2011;Martín-Buro et al, 2020;Michelmann et al, 2016;Waldhauser et al, 2016).…”

“…Fell et al, 2008;Griffiths et al, 2016;Hanslmayr et al, 2009), while the timing of the retrieval-related power decreases matches that of the retrieval success effect (e.g. Karlsson et al, 2020;Martín-Buro et al, 2020;Michelmann et al, 2016;Waldhauser et al, 2016).…”

“…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 et al, 2020;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).…”

The hippocampus as the switchboard between perception and memory

“…As shown in Figure 5 and Figure S6, juxtaposing the fMRI BOLD effects with the source-localised alpha power effects, both derived from the same memory paradigm, reveals a striking correspondence in the topography of the two measures. This result is consistent with the tight inverse relationship between fMRI BOLD and alpha power (Hermes et al, 2017;Laufs et al, 2003;Scheeringa et al, 2011) and corroborates the feasibility of source-localised M/EEG alpha power to study whole-brain memory dynamics (Martín-Buro et al, 2020). Capitalising on the time resolution of EEG, we next examined the temporal dynamics within the CRN.…”

“…That is, fMRI lacks the temporal resolution to pinpoint a hippocampal signal preceding target reinstatement, although recent analytical advances have yielded some progress in resolving finegrained memory dynamics with fMRI (Schuck and Niv, 2019;Staresina et al, 2013). Scalp EEG and MEG, combined with advanced source reconstruction methods (Gross, 2019;Michel et al, 2004), in principle provide adequate levels of spatial and temporal precision to uncover whole-brain memory dynamics (Bergström et al, 2013;Martín-Buro et al, 2020). However, ambiguities remain when interpreting activation in deeper sources such as the medial temporal lobe (MTL), at least without converging evidence from other imaging modalities.…”