Slow gamma oscillations (30–60 Hz) correlate with retrieval of spatial memory. Altered slow gamma oscillations have been observed in Alzheimer’s disease. Here, we use the J20-APP AD mouse model that displays spatial memory loss as well as reduced slow gamma amplitude and phase-amplitude coupling to theta oscillations phase. To restore gamma oscillations in the hippocampus, we used optogenetics to activate medial septal parvalbumin neurons at different frequencies. We show that optogenetic stimulation of parvalbumin neurons at 40 Hz (but not 80 Hz) restores hippocampal slow gamma oscillations amplitude, and phase-amplitude coupling of the J20 AD mouse model. Restoration of slow gamma oscillations during retrieval rescued spatial memory in mice despite significant plaque deposition. These results support the role of slow gamma oscillations in memory and suggest that optogenetic stimulation of medial septal parvalbumin neurons at 40 Hz could provide a novel strategy for treating memory deficits in AD.

No abstract

Despite many advances made in understanding the pathophysiology of epileptic disorders, seizures remain poorly controlled in approximately one-third of patients with mesial temporal lobe epilepsy. Here, we established the efficacy of cell type-specific low-frequency stimulation (LFS) in controlling ictogenesis in the mouse entorhinal cortex (EC) in an in vitro brain slice preparation. Specifically, we used 1 Hz optogenetic stimulation of calcium/calmodulin-dependent protein kinase II-positive principal cells as well as of parvalbuminor somatostatin-positive interneurons to study the effects of such repetitive activation on epileptiform discharges induced by 4-aminopyridine. We found that 1 Hz stimulation of any of these cell types reduced the frequency and duration of ictal discharges in some trials, while completely blocking them in others. The field responses evoked by the stimulation of each cell type revealed that their duration and amplitude were higher when principal cells were targeted. Furthermore, following a short period of silence ranging from 67 to 135 s, ictal discharges were re-established with similar duration and frequency as before stimulation; however, this period of silence was longer following principal cell stimulation compared with parvalbumin-or somatostatin-positive interneuron stimulation. Our results show that LFS of either excitatory or inhibitory cell networks in EC are effective in controlling ictogenesis. Although optogenetic stimulation of either cell type significantly reduced the occurrence of ictal discharges, principal cell stimulation resulted in a more prolonged suppression of ictogenesis, and, thus, it may constitute a better approach for controlling seizures.

Hippocampal control of memory formation is regulated by dopaminergic signaling. Whereas the role of dopamine D1 receptors is well documented in such regulations, functions of dopamine D2 receptors (DRD2) are not fully understood. Using fluorescence in situ hybridization we demonstrate that Drd2 expression in the hippocampus of wild-type mice is limited to glutamatergic hilar mossy cells. Using whole cell electrophysiological recordings in hippocampal slice preparations, we provide evidence that unlike in basal ganglia, activation of DRD2 by the selective agonist, quinpirole, induces a long-lasting increase in excitability of hilar mossy cells, which can be blocked by the DRD2 antagonist raclopride. Such activity is mediated by the Akt/GSK pathway, as application of specific inhibitors such as A1070722 or SB216763 prevented quinpirole activity. Long-term effects of acute DRD2 activation in vitro suggest that volume transmission of dopamine may modulate mossy cell activities in vivo. This is supported by the presence of dense tyrosine hydroxylase positive varicosities in the hilus, which are rarely seen in the vicinity of mossy cell dendrites. From these data we discuss how dopamine could control mossy cell activity and thus dentate gyrus functions.

Objective: To establish the effects induced by long-term, unilateral stimulation of parvalbumin (PV)-positive interneurons on seizures, interictal spikes, and high-frequency oscillations (80-500Hz) occurring after pilocarpine-induced status epilepticus (SE)-a proven model of mesial temporal lobe epilepsy (MTLE)-in transgenic mice expressing or not expressing ChR2. Methods: PV-ChR2 (n = 6) and PV-Cre (n = 6) mice were treated with pilocarpine to induce SE. Three hours after SE onset, unilateral optogenetic stimulation (450nm, 25mW, 20-millisecond pulses delivered at 8Hz for 30 seconds every 2 minutes) of CA3 PV-positive interneurons was implemented for 14 continuous days in both groups. Results: Rates of seizures (p < 0.01), interictal spikes (p < 0.001), and interictal spikes with fast ripples (250-500Hz) (p < 0.001) were lower in PV-ChR2 than in PV-Cre mice. Ripples (80-200Hz) occurring outside of interictal spikes had higher rates in the PV-ChR2 group (p < 0.01), whereas isolated fast ripples had lower rates (p < 0.01). However, seizure probability was higher during optogenetic stimulation in PV-ChR2 compared to PV-Cre animals (p < 0.05). Interpretation: Our findings show that the unilateral activation of CA3 PV-positive interneurons exerts anti-ictogenic effects associated with decreased rates of interictal spikes and fast ripples in this MTLE model. However, PV-positive interneuron stimulation can paradoxically trigger seizures in epileptic animals, supporting the notion that γ-aminobutyric acid type A signaling can also initiate ictogenesis. ANN NEUROL 2019;86:714-728 View this article online at wileyonlinelibrary.com.

Understanding the role of neuronal activity in cognition and behavior is a key question in neuroscience. Previously, in vivo studies have typically inferred behavior from electrophysiological data using probabilistic approaches including Bayesian decoding. While providing useful information on the role of neuronal subcircuits, electrophysiological approaches are often limited in the maximum number of recorded neurons as well as their ability to reliably identify neurons over time. This can be particularly problematic when trying to decode behaviors that rely on large neuronal assemblies or rely on temporal mechanisms, such as a learning task over the course of several days. Calcium imaging of genetically encoded calcium indicators has overcome these two issues. Unfortunately, because calcium transients only indirectly reflect spiking activity and calcium imaging is often performed at lower sampling frequencies, this approach suffers from uncertainty in exact spike timing and thus activity frequency, making rate-based decoding approaches used in electrophysiological recordings difficult to apply to calcium imaging data. Here we describe a probabilistic framework that can be used to robustly infer behavior from calcium imaging recordings and relies on a simplified implementation of a naive Baysian classifier. Our method discriminates between periods of activity and periods of inactivity to compute probability density functions (likelihood and posterior), significance and confidence interval, as well as mutual information. We next devise a simple method to decode behavior using these probability density functions and propose metrics to quantify decoding accuracy. Finally, we show that neuronal activity can be predicted from behavior, and that the accuracy of such reconstructions can guide the understanding of relationships that may exist between behavioral states and neuronal activity.

Understanding the role of neuronal activity in cognition and behavior is a key question in neuroscience. Previously, in vivo studies have typically inferred behavior from electrophysiological data using probabilistic approaches including bayesian decoding. While providing useful information on the role of neuronal subcircuits, electrophysiological approaches are often limited in the maximum number of recorded neurons as well as their ability to reliably identify neurons over time. This can be particularly problematic when trying to decode behaviors that rely on large neuronal assemblies or rely on temporal mechanisms, such as a learning task over the course of several days. Calcium imaging of genetically encoded calcium indicators has overcome these two issues. Unfortunately, because calcium transients only indirectly reflect spiking activity and calcium imaging is often performed at lower sampling frequencies, this approach suffers from uncertainty in exact spike timing and thus activity frequency, making rate-based decoding approaches used in electrophysiological recordings difficult to apply to calcium imaging data. Here we describe a simple probabilistic framework that can be used to robustly infer behavior from calcium imaging recordings. Our method discriminates periods of activity and periods of inactivity to compute conditional and unconditional probabilities. Neuronal activity can then be described in terms of joint probability, specificity, and confidence. We next devise a simple method to decode behavior from calcium activity and propose different metric to quantify decoding accuracy. Finally, we show that neuronal activity can be predicted from behavior, and that the accuracy of such reconstructions can guide the understanding of relationships that may exist between behavioral states and neuronal activity.

The hippocampal spatial code’s relevance for downstream neuronal populations—particularly its major subcortical output the lateral septum (LS)—is still poorly understood. Here, using calcium imaging combined with unbiased analytical methods, we functionally characterized and compared the spatial tuning of LS GABAergic cells to those of dorsal CA3 and CA1 cells. We identified a significant number of LS cells that are modulated by place, speed, acceleration, and direction, as well as conjunctions of these properties, directly comparable to hippocampal CA1 and CA3 spatially modulated cells. Interestingly, Bayesian decoding of position based on LS spatial cells reflected the animal’s location as accurately as decoding using the activity of hippocampal pyramidal cells. A portion of LS cells showed stable spatial codes over the course of multiple days, potentially reflecting long-term episodic memory. The distributions of cells exhibiting these properties formed gradients along the anterior–posterior and dorsal–ventral axes of the LS, directly reflecting the topographical organization of hippocampal inputs to the LS. Finally, we show using transsynaptic tracing that LS neurons receiving CA3 and CA1 excitatory input send projections to the hypothalamus and medial septum, regions that are not targeted directly by principal cells of the dorsal hippocampus. Together, our findings demonstrate that the LS accurately and robustly represents spatial, directional as well as self-motion information and is uniquely positioned to relay this information from the hippocampus to its downstream regions, thus occupying a key position within a distributed spatial memory network.