A model of working memory for encoding multiple items and ordered sequences exploiting the theta-gamma code

Modeling the contribution of theta-gamma coupling to sequential memory, imagination, and dreaming

Gamma oscillations nested in a theta rhythm are observed in the hippocampus, where are assumed to play a role in sequential episodic memory, i.e., memorization and retrieval of events that unfold in time. In this work, we present an original neurocomputational model based on neural masses, which simulates the encoding of sequences of events in the hippocampus and subsequent retrieval by exploiting the theta-gamma code. The model is based on a three-layer structure in which individual Units oscillate with a gamma rhythm and code for individual features of an episode. The first layer (working memory in the prefrontal cortex) maintains a cue in memory until a new signal is presented. The second layer (CA3 cells) implements an auto-associative memory, exploiting excitatory and inhibitory plastic synapses to recover an entire episode from a single feature. Units in this layer are disinhibited by a theta rhythm from an external source (septum or Papez circuit). The third layer (CA1 cells) implements a hetero-associative net with the previous layer, able to recover a sequence of episodes from the first one. During an encoding phase, simulating high-acetylcholine levels, the network is trained with Hebbian (synchronizing) and anti-Hebbian (desynchronizing) rules. During retrieval (low-acetylcholine), the network can correctly recover sequences from an initial cue using gamma oscillations nested inside the theta rhythm. Moreover, in high noise, the network isolated from the environment simulates a mind-wandering condition, randomly replicating previous sequences. Interestingly, in a state simulating sleep, with increased noise and reduced synapses, the network can "dream" by creatively combining sequences, exploiting features shared by different episodes. Finally, an irrational behavior (erroneous superimposition of features in various episodes, like "delusion") occurs after pathological-like reduction in fast inhibitory synapses. The model can represent a straightforward and innovative tool to help mechanistically understand the theta-gamma code in different mental states.

Utilizing tACS to enhance memory confidence and EEG to predict individual differences in brain stimulation efficacy

The information transfer necessary for successful memory retrieval is believed to be mediated by theta and gamma oscillations. These oscillations have been linked to memory processes in electrophysiological studies, which were correlational in nature. In the current study, we used transcranial alternating current stimulation (tACS) to externally modulate brain oscillations to examine its direct effects on memory performance. Participants received sham, theta (4 Hz), and gamma (50 Hz) tACS over frontoparietal regions while retrieving information in a source memory paradigm. Linear regression models were used to investigate the direct effects of oscillatory non-invasive brain stimulation (NIBS) on memory accuracy and confidence. Our results indicate that both theta and gamma tACS altered memory confidence. Specifically, theta tACS seemed to lower the threshold for confidence in retrieved information, while gamma tACS appeared to alter the memory confidence bias. Furthermore, the individual differences in tACS effects could be predicted from electroencephalogram (EEG) measures recorded prior to stimulation, suggesting that EEG could be a useful tool for predicting individual variability in the efficacy of NIBS.

The role of theta and gamma oscillations in item memory, source memory, and memory confidence

Theta and gamma oscillations have been linked to episodic memory processes in various studies. Both oscillations seem to be vital for processes guided by the medial temporal lobe, such as the retrieval of information from memory. While theta oscillations increase with successful memory, it is unclear what the unique contribution of theta is to various subcomponents of memory. On the other hand, memory-related gamma oscillations have been mainly reported in the hippocampus, leaving the role of neocortical gamma in memory underexplored. In the current study, we explored how unique variability in memory accuracy and memory confidence contributes to fluctuations in theta and gamma power. To this end, we recorded EEG from 54 participants while they performed a source memory task. From this task we obtained their item memory accuracy, source memory accuracy, item memory confidence, and source memory confidence. These behavioral measures were put in a trial-by-trial linear mixed effects model to uncover their unique contribution to the oscillatory power in frontal and parietal regions. Our results are in line with the involvement of theta oscillations in both memory accuracy and confidence, but seem to indicate a main role for theta oscillations in memory-related confidence. In addition, we found that gamma oscillations play various roles in memory-processing, dependent of brain region.

Rhythms of human attention and memory: An embedded process perspective

It remains a dogma in cognitive neuroscience to separate human attention and memory into distinct modules and processes. Here we propose that brain rhythms reflect the embedded nature of these processes in the human brain, as evident from their shared neural signatures: gamma oscillations (30-90 Hz) reflect sensory information processing and activated neural representations (memory items). The theta rhythm (3-8 Hz) is a pacemaker of explicit control processes (central executive), structuring neural information processing, bit by bit, as reflected in the theta-gamma code. By representing memory items in a sequential and time-compressed manner the theta-gamma code is hypothesized to solve key problems of neural computation: (1) attentional sampling (integrating and segregating information processing), (2) mnemonic updating (implementing Hebbian learning), and (3) predictive coding (advancing information processing ahead of the real time to guide behavior). In this framework, reduced alpha oscillations (8-14 Hz) reflect activated semantic networks, involved in both explicit and implicit mnemonic processes. Linking recent theoretical accounts and empirical insights on neural rhythms to the embedded-process model advances our understanding of the integrated nature of attention and memory - as the bedrock of human cognition.