Cholinergic modulation of Up–Down states in the mouse medial entorhinal cortex in vitro

Cholinergic tone is high during wake and rapid eye movement sleep and lower during slow wave sleep (SWS). Nevertheless, the low tone of acetylcholine during SWS modulates sharp wave ripple incidence in the hippocampus and slow wave activity in the neocortex. Linking the hippocampus and neocortex, the medial entorhinal cortex (mEC) regulates the coupling between these structures during SWS, alternating between silent Down states and active Up states, which outlast neocortical ones. Here, we investigated how low physiological concentrations of acetylcholine (ACh; 100‐500 nM) modulate Up and Down states in a mEC slice preparation. We find that ACh has a dual effect on mEC activity: it prolongs apparent Up state duration as recorded in individual cells and decreases the total synaptic charge transfer, without affecting the duration of detectable synaptic activity. The overall outcome of ACh application is excitatory and we show that ACh increases Up state incidence via muscarinic receptor activation. The mean firing rate of principal neurons increased in around half of the cells while the other half showed a decrease in firing rate. Using two‐photon calcium imaging of population activity, we found that population‐wide network events are more frequent and rhythmic during ACh and confirmed that ACh modulates cell participation in these network events, consistent with a role for cholinergic modulation in regulating information flow between the hippocampus and neocortex during SWS

Explicit-Duration Hidden Markov Model Inference of UP-DOWN States from Continuous Signals

Neocortical neurons show UP-DOWN state (UDS) oscillations under a variety of conditions. These UDS have been extensively studied because of the insight they can yield into the functioning of cortical networks, and their proposed role in putative memory formation. A key element in these studies is determining the precise duration and timing of the UDS. These states are typically determined from the membrane potential of one or a small number of cells, which is often not sufficient to reliably estimate the state of an ensemble of neocortical neurons. The local field potential (LFP) provides an attractive method for determining the state of a patch of cortex with high spatio-temporal resolution; however current methods for inferring UDS from LFP signals lack the robustness and flexibility to be applicable when UDS properties may vary substantially within and across experiments. Here we present an explicit-duration hidden Markov model (EDHMM) framework that is sufficiently general to allow statistically principled inference of UDS from different types of signals (membrane potential, LFP, EEG), combinations of signals (e.g., multichannel LFP recordings) and signal features over long recordings where substantial non-stationarities are present. Using cortical LFPs recorded from urethane-anesthetized mice, we demonstrate that the proposed method allows robust inference of UDS. To illustrate the flexibility of the algorithm we show that it performs well on EEG recordings as well. We then validate these results using simultaneous recordings of the LFP and membrane potential (MP) of nearby cortical neurons, showing that our method offers significant improvements over standard methods. These results could be useful for determining functional connectivity of different brain regions, as well as understanding network dynamics

Laminar analysis of the slow wave activity in the somatosensory cortex of anesthetized rats.

Rhythmic slow waves characterize brain electrical activity during natural deep sleep and under anesthesia, reflecting the synchronous membrane potential fluctuations of neurons in the thalamocortical network. Strong evidence indicates that the neocortex plays an important role in the generation of slow wave activity (SWA), however, contributions of individual cortical layers to the SWA generation are still unclear. The anatomically correct laminar profiles of SWA were revealed under ketamine/xylazine anesthesia, with combined local field potential recordings, multiple-unit activity (MUA), current source density (CSD) and time-frequency analyses precisely co-registered with histology. The up-state related negative field potential wave showed the largest amplitude in layer IV, the CSD was largest in layers I and III, while MUA was maximal in layer V, suggesting spatially dissociated firing and synaptic/transmembrane processes in the rat somatosensory cortex. Up-state related firing could start in virtually any layers (III-VI) of the cortex, but were most frequently initiated in layer V. However, in a subset of experiments, layer IV was considerably active in initiating up-state related MUA even in the absence of somatosensory stimulation. Somatosensory stimulation further strengthened up-state initiation in layer IV. Our results confirm that cortical layer V firing may have a major contribution to the up-state generation of ketamine/xylazine-induced SWA, however, thalamic influence through the thalamorecipient layer IV can also play an initiating role, even in the absence of sensory stimulation. This article is protected by copyright. All rights reserved

Sensory information processing in mouse barrel cortex

Processazione dell'informazione sensoriale nella "barrel cortex" di top