The Hybrid Drive: a chronic implant device combining tetrode arrays with silicon probes for layer-resolved ensemble electrophysiology in freely moving mice

In vivo recordings in freely behaving mice using independent silicon probes targeting multiple brain regions

In vivo recordings in freely behaving animals are crucial to understand the neuronal circuit basis of behavior. Although current multi-channel silicon probes provide unparalleled sampling density, the study of interacting neuronal populations requires the implantation of multiple probes across different regions of the brain. Ideally, these probes should be independently adjustable, to maximize the yield, and recoverable, to mitigate costs. In this work, we describe the implementation of a miniaturized 3D-printed headgear system for chronic in vivo recordings in mice using independently movable silicon probes targeting multiple brain regions. We successfully demonstrated the performance of the headgear by simultaneously recording the neuronal activity in the prelimbic cortex and dorsal hippocampus. The system proved to be sturdy, ensuring high-quality stable recordings and permitted reuse of the silicon probes, with no observable interference in mouse innate behaviors.

Protocol for geometric transformation of cognitive maps for generalization across hippocampal-prefrontal circuits

Memory generalization is the ability to abstract knowledge from prior experiences and is critical for flexible behavior in novel situations. Here, we describe a protocol for simultaneous recording of hippocampal (area CA1)-prefrontal cortical neural ensembles in Long-Evans rats during task generalization across two distinct environments. We describe steps for building and assembling experimental apparatuses, animal preparation and surgery, and performing experiments. We then detail procedures for histology, data processing, and assessing population geometry using Uniform Manifold Approximation and Projection. For complete details on the use and execution of this protocol, please refer to Tang et al. (2023).1.

State-dependent coupling of hippocampal oscillations

Oscillations occurring simultaneously in a given area represent a physiological unit of brain states. They allow for temporal segmentation of spikes and support distinct behaviors. To establish how multiple oscillatory components co-vary simultaneously and influence neuronal firing during sleep and wakefulness in mice, we describe a multivariate analytical framework for constructing the state space of hippocampal oscillations. Examining the co-occurrence patterns of oscillations on the state space, across species, uncovered the presence of network constraints and distinct set of cross-frequency interactions during wakefulness compared to sleep. We demonstrated how the state space can be used as a canvas to map the neural firing and found that distinct neurons during navigation were tuned to different sets of simultaneously occurring oscillations during sleep. This multivariate analytical framework provides a window to move beyond classical bivariate pipelines for investigating oscillations and neuronal firing, thereby allowing to factor-in the complexity of oscillation-population interactions.

Heterogeneity of network and coding states in mouse CA1 place cells

Theta sequences and phase precession shape hippocampal activity and are considered key underpinnings of memory formation. Theta sequences are sweeps of spikes from multiple cells, tracing trajectories from past to future. Phase precession is the correlation between theta firing phase and animal position. Here, we reconsider these temporal processes in CA1 and the computational principles that they are thought to obey. We find stronger heterogeneity than previously described: we identify cells that do not phase precess but reliably express theta sequences. Other cells phase precess only when medium gamma (linked to entorhinal inputs) is strongest. The same cells express more sequences, but not precession, when slow gamma (linked to CA3 inputs) dominates. Moreover, sequences occur independently in distinct cell groups. Our results challenge the view that phase precession is the mechanism underlying the emergence of theta sequences, suggesting a role for CA1 cells in multiplexing diverse computational processes.