Cell assemblies

Assessing how brain activity generalizes across individuals is a central challenge in experimental neuroscience. Traditional task- or stimulus-driven approaches align data through trial averaging and anatomical registration, but these methods fail for spontaneous activity, where no shared temporal reference exists. In this talk, I will introduce a statistical framework, called latent-aligned Restricted Boltzmann Machines, to build a common representational space from whole-brain recordings of spontaneous activity in multiple zebrafish larvae. This shared latent space, composed of spatially loc

…Cell assemblies, or engrams, may provide neural representations for such relationships. First, I will show a class of associative memory models that encode and retrieve multiple memory contents linked by an arbitrary graph structure through experience and demonstrate the crucial role of the balance between two inhibitory subnet

…They suggest the existence of cell assemblies, groups of co-active neurons that represent a distinct cognitive unit, potentially related to specific behaviors or representations. Conventionally, cell assemblies are defined by strong structural connections, such that the stimulation of a portion of its members should transiently activate the entire assembly. Their exact composition and computational role, however, have yet to be fully clarified. We present the detection of spik

Prior neuroimaging studies have shown that words associated with actions, like "grasp" and "kick," activate specific regions in the cortical motor system corresponding to the body parts involved in those actions. This activation follows the somatotopic mapping of these body parts. The variation in activation could suggest differences in how different types of symbols are processed semantically, or it might be a byproduct of activities related to imagining scenes associated with the meanings of these symbols. To address this debate, we simulated the semantic learning of realistic action words i

The brain continuously encodes new information as memories. At the synaptic level, memory formation is enabled by adjusting connections between activated excitatory neurons in the cortex, with mirroring inhibitory activity ensuring stable storage. Particularly, synaptic plasticity occurs as memory reactivation takes place during sleep, contributing to increased memory stability. However, the mechanism by which reactivation mediates plasticity to balance network currents for stable memory storage remains unclear. Here, we investigated whether a newly proposed form of codependent plasticity coul

Spatial memory consolidation is supported by the coupling of hippocampus (HPC) and medial prefrontal cortex (mPFC) activities during sleep. The thalamic nucleus reuniens (NR), reciprocally connected to the HPC and the mPFC, is thought to play a key role in this process. In order to characterize the interactions of these structures during memory consolidation, we developed a new experimental protocol. On an automated maze, animals learn a daily trajectory to a reward and are tested for performance in subsequent sleep. During this protocol, we conduct high-density recording of the HPC, NR and mP

…groups of neurons, known as cell assemblies. Our team demonstrated the existence of reader neurons, responsive to the activity of cell assemblies from upstream brain structures, and showed that functional links between assemblies and their readers are modified through learning processes. On the other hand, there is accumulating evidence that brain-wide dynamics are characterized by neuronal avalanches, namely aperiodic bursts of activity spreading across the population

…activity waves, reflecting distinct cell assemblies that encoded olfaction-only, duration-only, or both information. The regional proportion of neurons and wave timing within cell ass

…of heavily interconnected cell assemblies and showcased its beneficial consequences for memories. However, to be maintained, the memories needed frequent reactivations such that the weights within the assemblies remain at a high level. In this work, we extend the model such that memories are maintained independently of reactivations. We suggest that long-term memories are mainly represented by the number of connections between assembly