Memory consolidation by replay of stimulus-specific neural activity.

Memory consolidation transforms initially labile memory traces into more stable representations. One putative mechanism for consolidation is the reactivation of memory traces after their initial encoding during subsequent sleep or waking state. However, it is still unknown whether consolidation of individual memory contents relies on reactivation of stimulus-specific neural representations in humans. Investigating stimulus-specific representations in humans is particularly difficult, but potentially feasible using multivariate pattern classification analysis (MVPA). Here, we show in healthy human participants that stimulus-specific activation patterns can indeed be identified with MVPA, that these patterns reoccur spontaneously during postlearning resting periods and sleep, and that the frequency of reactivation predicts subsequent memory for individual items. We conducted a paired-associate learning task with items and spatial positions and extracted stimulus-specific activity patterns by MVPA in a simultaneous electroencephalography and functional magnetic resonance imaging (fMRI) study. As a first step, we investigated the amount of fMRI volumes during rest that resembled either one of the items shown before or one of the items shown as a control after the resting period. Reactivations during both awake resting state and sleep predicted subsequent memory. These data are first evidence that spontaneous reactivation of stimulus-specific activity patterns during resting state can be investigated using MVPA. They show that reactivation occurs in humans and is behaviorally relevant for stabilizing memory traces against interference. They move beyond previous studies because replay was investigated on the level of individual stimuli and because reactivations were not evoked by sensory cues but occurred spontaneously.

Hippocampal control of repetition effects for associative stimuli.

Recent findings suggest that repetition effects interact with episodic memory processes that are putatively supported by the hippocampus. Thus, the formation or refinement of episodic memories may be related to a modulating signal from the hippocampus to the neocortex which leads to sparser or more extended stimulus representations (repetition suppression or enhancement), depending on the type of stimulus and the brain site. This framework suggests that hippocampal activity during the initial presentation of a stimulus correlates with the magnitude of repetition effects. Here, we tested this hypothesis in an fMRI study in which associations between faces and buildings were presented twice. BOLD responses showed repetition suppression in fusiform face area (FFA) and parahippocampal place area (PPA), most likely due to a refinement of existing category representations. Hippocampal activity during the first presentations was correlated with the amount of repetition suppression, in particular in the FFA. Repetition enhancement effects were observed on BOLD responses in posterior parietal cortex, possibly related to the formation of new representations of associative stimuli. The magnitude of parietal BOLD repetition effects depended on successful memory formation. These findings suggest that both repetition enhancement and repetition suppression effects are influenced by a modulating signal from the hippocampus.

Inferring directional interactions from transient signals with symbolic transfer entropy.

We extend the concept of symbolic transfer entropy to enable the time-resolved investigation of directional relationships between coupled dynamical systems from short and transient noisy time series. For our approach, we consider an observed ensemble of a sufficiently large number of time series as multiple realizations of a process. We derive an index that quantifies the preferred direction of transient interactions and assess its significance using a surrogate-based testing scheme. Analyzing time series from noisy chaotic systems, we demonstrate numerically the applicability and limitations of our approach. Our findings obtained from an analysis of event-related brain activities underline the importance of our method to improve understanding of gross neural interactions underlying cognitive processes.

Ventromedial prefrontal cortex activation is associated with memory formation for predictable rewards.

During reinforcement learning, dopamine release shifts from the moment of reward consumption to the time point when the reward can be predicted. Previous studies provide consistent evidence that reward-predicting cues enhance long-term memory (LTM) formation of these items via dopaminergic projections to the ventral striatum. However, it is less clear whether memory for items that do not precede a reward but are directly associated with reward consumption is also facilitated. Here, we investigated this question in an fMRI paradigm in which LTM for reward-predicting and neutral cues was compared to LTM for items presented during consumption of reliably predictable as compared to less predictable rewards. We observed activation of the ventral striatum and enhanced memory formation during reward anticipation. During processing of less predictable as compared to reliably predictable rewards, the ventral striatum was activated as well, but items associated with less predictable outcomes were remembered worse than items associated with reliably predictable outcomes. Processing of reliably predictable rewards activated the ventromedial prefrontal cortex (vmPFC), and vmPFC BOLD responses were associated with successful memory formation of these items. Taken together, these findings show that consumption of reliably predictable rewards facilitates LTM formation and is associated with activation of the vmPFC.