Gamma - Theta - Spike Coupling Coordinates Sequential Memory in Human MTL
Prakash, M. J.; Niediek, J.; Surges, R.; Mormann, F.; Liebe, S.
Show abstract
It has been suggested that hierarchical synchronization of theta and gamma oscillations coordinates neural activity during sequence memory. Yet, the role of gamma oscillations and their interaction with theta and single-unit activity (SUA) has not been directly examined in humans. We analysed simultaneous micro wire recordings of single-unit activity (N = 1417) and local field potentials (N = 917 channels) from the medial temporal lobe (MTL) of epilepsy patients performing a visual multi-item sequence memory task. During encoding, both spiking activity and gamma power contained item-specific information and were temporally coupled. During memory maintenance, stimulus-specific gamma was characterized by recurring bursts during which spiking was tightly synchronized and both, gamma and spiking, were preferentially aligned to similar theta phases predictive of sequential stimulus position. These findings demonstrate that theta-gamma-spike interactions support a phase-based multiplexed code for sequential memories in the human MTL.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Smell-induced gamma oscillations in human olfactory cortex are required for accurate perception of odor identity 95%
- Neural activity during a simple reaching task in macaques is counter to gating and rebound in basal ganglia-thalamic communication 95%
- Sustained neural rhythms reveal endogenous oscillations supporting speech perception 94%
Similar papers in this journal
- Face-selective units in human ventral temporal cortex reactivate during free recall 95%
- Stimulus-induced theta band LFP oscillations format neuronal representations of social chemosignals in the mouse accessory olfactory bulb 94%
- Cell assemblies in the cortico-hippocampal-reuniens network during slow oscillations 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.