Developments in microfabrication technology have enabled the production of neural electrode arrays with hundreds of closely-spaced recording sites, and electrodes with thousands of sites are currently under development. These probes in principle allow the simultaneous recording of very large numbers of neurons. However, use of this technology requires the development of techniques for decoding the spike times of the recorded neurons, from the raw data captured from the probes. Here, we present a set of novel tools to solve this problem, implemented in a suite of practical, user-friendly, open-source software. We validate these methods on data from the cortex, hippocampus, and thalamus of rat, mouse, macaque, and marmoset, demonstrating error rates as low as 5%.

Cell assembly sequences during learning are “replayed” during hippocampal ripples and contribute to the consolidation of episodic memories. However, neuronal sequences may also reflect preexisting dynamics. We report that sequences of place-cell firing in a novel environment are formed from a combination of the contributions of a rigid, predominantly fast-firing subset of pyramidal neurons with low spatial specificity and limited change across sleep-experience-sleep and a slow-firing plastic subset. Slow-firing cells, rather than fast-firing cells, gained high place specificity during exploration, elevated their association with ripples, and showed increased bursting and temporal coactivation during postexperience sleep. Thus, slow- and fast-firing neurons, although forming a continuous distribution, have different coding and plastic properties.

SUMMARY Sleep is composed of an alternating sequence of REM and non-REM episodes, but their respective roles are not known. We found that the overall firing rates of hippocampal CA1 neurons decreased across sleep concurrent with an increase in the recruitment of neuronal spiking to brief “ripple” episodes, resulting in a net increase in neural synchrony. Unexpectedly, within non-REM episodes, overall firing rates gradually increased together with a decrease in the recruitment of spiking to ripples. The rate increase within non-REM episodes was counteracted by a larger and more rapid decrease of discharge frequency within the interleaved REM episodes. Both the decrease in firing rates and the increase in synchrony during the course of sleep were correlated with the power of theta activity during REM episodes. These findings assign a prominent role of REM sleep in sleep-related neuronal plasticity.

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Diverse computations in the neocortex are aided by specialized GABAergic interneurons (INs), which selectively target other INs. However, much less is known about how these canonical disinhibitory circuit motifs contribute to network operations supporting spatial navigation and learning in the hippocampus. Using chronic two-photon calcium imaging in mice performing random foraging or goal-oriented learning tasks, we found that vasoactive intestinal polypeptide-expressing (VIP +), disinhibitory INs in hippocampal area CA1 form functional subpopulations defined by their modulation by behavioral states and task demands. Optogenetic manipulations of VIP + INs and computational modeling further showed that VIP + disinhibition is necessary for goaldirected learning and related reorganization of hippocampal pyramidal cell population dynamics. Our results demonstrate that disinhibitory circuits in the hippocampus play an active role in supporting spatial learning.

Hippocampal place cells represent the cellular substrate of episodic memory. Place cell ensembles reorganize to support learning but must also maintain stable representations to facilitate memory recall. Despite extensive research, the learning-related role of place cell dynamics in health and disease remains elusive. Using chronic two-photon Ca2+ imaging in hippocampal area CA1 of wild-type and Df(16)A+/− mice, an animal model of 22q11.2 deletion syndrome, one of the most common genetic risk factors for cognitive dysfunction and schizophrenia, we found that goal-oriented learning in wild-type mice was supported by stable spatial maps and robust remapping of place fields toward the goal location. Df(16)A+/− mice showed a significant learning deficit accompanied by reduced spatial map stability and the absence of goal-directed place cell reorganization. These results expand our understanding of the hippocampal ensemble dynamics supporting cognitive flexibility and demonstrate their importance in a model of 22q11.2-associated cognitive dysfunction.

A major challenge in neuroscience is linking behavior to the collective activity of neural assemblies. Understanding of input-output relationships of neurons and circuits requires methods with the spatial selectivity and temporal resolution appropriate for mechanistic analysis of neural ensembles in the behaving animal, i.e. recording of representatively large samples of isolated single neurons. Ensemble monitoring of neuronal activity has progressed remarkably in the past decade in both small and large-brained animals, including human subjects 1-11 . Multiple-site recording with silicon-based devices are particularly effective because of their scalability, small volume and geometric design.

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