Neural Context Reinstatement of Recurring Events.

Episodic recollection involves retrieving context information bound to specific events. However, autobiographical memory largely comprises recurrent, similar experiences that become integrated into joint representations. In the current study, we extracted a neural signature of temporal context from scalp electroencephalography (EEG) to investigate whether recalling a recurring event accompanies the reinstatement of one or multiple instances of its occurrence.

Novel TSPO Ligand 2-Cl-MGV-1 Can Counteract Lipopolysaccharide Induced Inflammatory Response in Murine RAW264.7 Macrophage Cell Line and Lung Models.

We assessed the anti-inflammatory activity of the TSPO ligand 2-Cl-MGV-1. Lipopolysaccharide (LPS) was used to induce inflammatory response in a murine RAW264.7 macrophage model (LPS: 100 ng/mL) and a mouse model (C57BL/6) of lung inflammation (LPS: 5 mg/kg).

Neural correlates of memory in a naturalistic spatiotemporal context.

We investigated memory encoding and retrieval during a quasinaturalistic spatial-episodic memory task in which subjects delivered items to landmarks in a desktop virtual environment and later recalled the delivered items. Transition probabilities and latencies revealed the spatial and temporal organization of memory. As subjects gained experience with the town, their improved spatial knowledge led to more efficient navigation and increased spatial organization during recall.

A preserved neural code for temporal order between memory formation and recall in the human medial temporal lobe.

Temporal memory enables us to remember the temporal order of events happening in our life. The human medial temporal lobe (MTL) appears to contain neural representations supporting temporal memory formation, but the cellular mechanisms that preserve temporal order information for recall are largely unknown. Here, we examined whether human MTL neuronal activity represents the temporal position of events during memory formation and recall, using invasive single and multi-unit recordings in human epilepsy patients (n = 19).

Decoding EEG for optimizing naturalistic memory.

Background: Spectral features of human electroencephalographic (EEG) recordings during learning predict subsequent recall variability.

New Method: Capitalizing on these fluctuating neural features, we develop a non-invasive closed-loop (NICL) system for real-time optimization of human learning. Participants play a virtual navigation-and-memory game; recording multi-session data across days allowed us to build participant-specific classification models of recall success.