Dissociation of LFP Power and Tuning in the Frontal Cortex during Memory

Abstract

Working memory, the ability to maintain and manipulate information in the brain, is critical for cognition. During the memory period of spatial memory tasks, neurons in the prefrontal cortex code for memorized locations via persistent, spatially tuned increases in activity. Local field potentials (LFPs) are understood to reflect summed synaptic activity of local neuron populations and may offer a window into network-level processing. We recorded LFPs from areas 8A and 9/46 while two male cynomolgus macaques () performed a long duration (5.1-15.6 s) memory-guided saccade task. Greater than ∼16 Hz, LFP power was contralaterally tuned throughout the memory period. Yet power for both contralateral and ipsilateral targets fell gradually after the first second of the memory period, dropping below baseline after a few seconds. Our results dissociate absolute LFP power from mnemonic tuning and are consistent with modeling work that suggests that decreasing synchronization within a network may improve the stability of memory coding. The frontal cortex is an important site for working memory. There, individual neurons reflect memorized information with selective increases in activity, but how collections of neurons work together to achieve memory is not well understood. In this work, we examined rhythmic electrical activity surrounding these neurons, which may reflect the operation of recurrent circuitry that could underlie memory. This rhythmic activity was spatially tuned with respect to memorized locations as long as memory was tested (∼7.5 s). Surprisingly, however, the overall magnitude of rhythmic activity decreased steadily over this period, dropping below baseline levels after a few seconds. These findings suggest that collections of neurons may actively desynchronize to promote stability in memory circuitry.

Local field potentials reflect cortical population dynamics in a region-specific and frequency-dependent manner

“…First, since LFP [6][7][8][9][10] and latent dynamics 20,21,27 are shaped by the circuit biophysics (Figure 1B), we expect to find a robust relationship between these two signals. Second, this relationship should be frequency-dependent, because only specific LFP bands are strongly correlated with the behaviour [28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44]51 . Third, given that the synaptic connections remain stable in the short time scale spanning the preparation and execution of a movement, we anticipate the various LFP-latent dynamics associations would remain similarly stable throughout these two processes underlying behaviour.…”

“…Currents through these same connections are the main contributors to the generation of the LFPs 6-10 (Figure 1A). In particular, correlations in the synaptic input currents across the population yield changes in LFP power at specific frequency bands, which often relate to specific brain functions [28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44] . For example, in the motor cortices, movement-related information lies primarily at low and high frequencies [36][37][38][39] (i.e.…”

Dissociation of dorso-lateral and dorso-medial prefrontal cortex contributions to familiarity and recollective processes in primates

“…This gives support to hence our external source of beta frequency entrainment from rTMS over the same region may have impaired recognition memory performance by lessening natural processes of de-synchronization as this hypothesis predicts. Holmes et al (2018) also showed a dissociation between LFP beta power and mnemonic tuning and whilst in a spatial task this is also consistent with de-synchronization aiding memory stability (Holmes et al, 2018). Neural attractor network modeling (Compte et al, 2003), in the context of delayed response task performance in NHPs, also suggests mechanisms by which a drop in LFP power may relate to memory processing; asynchronous networks can maintain memory coding for longer durations whereas synchronization leads to an overall instabilities incompatible with stable memory-coding states.…”

“…A rationale, based on information theory, is that synchronization of neural firings reduces the richness of information transfer which results in information redundancy; in contrast, a desynchronization of neural firing patterns leads to more potential for carrying information to improve the efficiency of neural communications (Simon Hanslmayr et al, 2012). The desynchronization hypothesis, applied to human recognition memory and our paradigm, maintains that a decrease of alpha/beta power may be associated with more efficient encoding, which helps contribute to successful memory retrieval subsequently (Simon Holmes et al, 2018). Therefore we first hypothesized that in our human investigations of a similar task to that performed by the NHP (albeit with lists of samples followed by lists of choice trials to increase memory demands so to avoid ceiling effects) that interfering in efficient beta desynchronization would be deleterious to successful encoding and hence recognition performance.…”

“…It's relation to performance was determined by confirming that the power was significantly higher in trials than proceeded to be correct trials (in the subsequent choice phase) than in trials that proceeded to be error trials. The desynchronization hypothesis (Simon Hanslmayr et al, 2012;Holmes et al, 2018) suggests that PFC neurons desynchronize to retain stable memories. We observed robust beta power that was greater in 9 correct trials but which didn't persist throughout the entire sample presentation; therefore it may be hypothesized accordingly that transient robust beta power coupled with subsequent efficient beta power desynchronization supports effective memory encoding.…”