@article {68588, title = {Functional specialization and structured representations for space and time in prefrontal cortex}, journal = {bioRxiv}, year = {2023}, month = {2023 Jan 18}, abstract = {

Individual neurons in prefrontal cortex {\textendash} a key brain area involved in cognitive functions {\textendash} are selective for variables such as space or time, as well as more cognitive aspects of tasks, such as learned categories. Many neurons exhibit mixed selectivity, that is, they show selectivity for multiple variables. A fundamental question is whether neurons are functionally specialized for particular variables and how selectivity for different variables intersects across the population. Here, we analyzed neural correlates of space and time in rats performing a navigational task with two behaviorally important categories {\textendash} starts and goals. Using simultaneous recordings of many medial prefrontal cortex (mPFC) neurons during behavior, we found that population codes for elapsed time were invariant to different locations within categories, and subsets of neurons had functional preferences for time or space across categories. Thus, mPFC exhibits structured selectivity, which may facilitate complex behaviors by efficiently generating informative representations of multiple variables.

}, doi = {10.1101/2023.01.16.524214}, url = {https://doi.org/10.1101/2023.01.16.524214}, author = {Claudia B{\"o}hm and Albert K. Lee} } @article {69009, title = {Low-latency extracellular spike assignment for high-density electrodes at single-neuron resolution}, journal = {bioRxiv}, year = {2023}, month = {2023 Sep 15}, abstract = {

Real-time neural signal processing is essential for brain-machine interfaces and closed-loop neuronal perturbations. However, most existing applications sacrifice cell-specific identity and temporal spiking information for speed. We developed a hybrid hardware-software system that utilizes a Field Programmable Gate Array (FPGA) chip to acquire and process data in parallel, enabling individual spikes from many simultaneously recorded neurons to be assigned single-neuron identities with 1-millisecond latency. The FPGA assigns labels, validated with ground-truth data, by comparing multichannel spike waveforms from tetrode or silicon probe recordings to a spike-sorted model generated offline in software. This platform allowed us to rapidly inactivate a region in vivo based on spikes from an upstream neuron before these spikes could excite the downstream region. Furthermore, we could decode animal location within 3 ms using data from a population of individual hippocampal neurons. These results demonstrate our system{\textquoteright}s suitability for a broad spectrum of research and clinical applications.

}, doi = {10.1101/2023.09.14.557854}, url = {https://doi.org/10.1101/2023.09.14.557854}, author = {Chongxi Lai and Dohoung Kim and Brian Lustig and Shinsuke Tanaka and Brian Barbarits and Lakshmi Narayan and Jennifer Colonell and Ole Paulsen and Albert K. Lee and Timothy D. Harris} } @article {68700, title = {Mental navigation and telekinesis with a hippocampal map-based brain-machine interface}, journal = {bioRxiv}, year = {2023}, month = {2023 Apr 10}, abstract = {

The hippocampus is critical for recollecting and imagining experiences. This is believed to involve voluntarily drawing from hippocampal memory representations of people, events, and places, including the hippocampus{\textquoteright} map-like representations of familiar environments. However, whether the representations in such {\textquotedblleft}cognitive maps{\textquotedblright} can be volitionally and selectively accessed is unknown. We developed a brain-machine interface to test if rats could control their hippocampal activity in a flexible, goal-directed, model-based manner. We show that rats can efficiently navigate or direct objects to arbitrary goal locations within a virtual reality arena solely by activating and sustaining appropriate hippocampal representations of remote places. This should provide insight into the mechanisms underlying episodic memory recall, mental simulation/planning, and imagination, and open up possibilities for high-level neural prosthetics utilizing hippocampal representations.

}, doi = {10.1101/2023.04.07.536077}, url = {https://doi.org/10.1101/2023.04.07.536077}, author = {Chongxi Lai and Shinsuke Tanaka and Timothy D. Harris and Albert K. Lee} }