Article Figures & Data
Figures
- Figure 1.
Location of microperfusion sites and prediction of the anatomic extent of muscimol-mediated inhibition. A, Example site of microperfusion located at the boundary of the vlPAG and the DpMe. The black arrow indicates the most ventral point of the lesion left by the microdialysis probe. B, Probe locations sites for all 25 rats (blue rectangles = muscimol group; red rectangles = control group) located between the anterioposterior level defined by the caudal pole of the paratrochlear nucleus to the caudal extent of the superior cerebellar peduncle decussation. All probes were implanted on the right side; probes positions are shown on both sides for clarity purposes. C, Results of our simulation-based estimate of average PSI across all experiments in stereotaxic coordinate space.
- Figure 2.
Control group validation of the NRt scoring method. A, Compared levels of wake, NREM, and REM sleep between periods 1 (ZT3 and ZT5) and 2 (ZT5.5 and ZT7.5) in the control group (n = 13). B, Same data as in A, except the NRt scoring method is used. C, Same data as in B, except levels of sleep are expresses as a percentage of TST rather than TRT. For each comparison, the paired mean differences are shown in Cumming estimation plots. The raw data are plotted on the upper axes; each paired set of observations is connected by a line. On the lower axes, each paired mean difference is plotted as a bootstrap sampling distribution. Mean differences are depicted as dots; 95% CIs are indicated by the ends of the vertical error bars. The algorithm for defining NREM-to-REM sleep transition dynamics is illustrated in Extended Data Figure 2-1.
- Figure 3.
Effects of vlPAG/DpMe inhibition on sleep macroarchitecture and bistability. A, Effects of vlPAG/DpMe inhibition on the levels of sleep-wake states as a proportion of the TRT. Levels of REM sleep are given for both 3-stage scoring and 4-stage NRt scoring. B, Effects of vlPAG/DpMe inhibition on the levels of REM sleep and NRt states as a proportion of the TST. Levels of REM sleep are given for both 3-stage scoring and 4-stage NRt scoring. For each comparison, the paired mean differences are shown in Cumming estimation plots. The raw data are plotted on the upper axes; each paired set of observations is connected by a line. On the lower axes, each paired mean difference is plotted as a bootstrap sampling distribution. Mean differences are depicted as dots; 95% CIs are indicated by the ends of the vertical error bars.
- Figure 4.
Effects of vlPAG/DpMe inhibition on bout frequency and length. The effects of vlPAG/DpMe inhibition on bout frequency and length for (A, B) REM sleep, (C, D) NRt, (E, F) NREM sleep, and (G, H) wake. For each state, we give the total number of bouts, the number of short bouts and the number of long bouts for the ACSF and muscimol conditions (A, C, E). For each comparison, the paired mean differences are shown in Cumming estimation plots. The raw data are plotted on the upper axes; each paired set of observations is connected by a line. On the lower axes, each paired mean difference is plotted as a bootstrap sampling distribution. Mean differences are depicted as dots; 95% CIs are indicated by the ends of the vertical error bars. Also, for each state, bout length histograms are provided in B, D, F showing the cumulative bout numbers across all 12 rats in the muscimol group.
- Figure 5.
Hypnograms for all transitions into REM sleep. Shown are the hypnograms for all transitions into REM sleep from all rats numbered 1–12, inclusive of REM sleep episodes and the preceding 90 s. All transitions are aligned according to the epoch where the transition into REM sleep takes place (denoted as time 0).
- Figure 6.
NRt dynamics in NREM versus REM sleep. A–D, Exemplar state-space plot from a single experiment. A, All NRt trajectories originating in NREM sleep space during the baseline period. B, Trajectory of the only excursion into NRT space originating in REM sleep over the same period in the same animal. C, D, Examples of the NRt trajectories originating, from NREM and REM sleep, respectively, during muscimol-mediated inhibition of the vlPAG/DpMe. E, Group data of paired mean difference in NRt density originating in NREM sleep (NRt bouts/minutes of NREM sleep) and REM sleep (NRt bouts/minutes of REM sleep). F, Total NRt amount as a percentage of TST for NRt originating in NREM and REM sleep. G, Average NRt bout duration for NRt originating in NREM and REM sleep. Paired mean differences are shown for all comparisons in a Cumming estimation plot. The raw data are plotted on the upper axes; each paired set of observations is connected by a line. On the lower axes, each paired mean difference is plotted as a bootstrap sampling distribution. Mean differences are depicted as dots; 95% CIs are indicated by the ends of the vertical error bars.
- Figure 7.
EEG effects of vlPAG/DpMe inhibition. Group data showing the effect of muscimol on relative EEG power (in 2-Hz-wide bins from 1 to 19 Hz). A, Comparison of EEG power between NRt and both NREM and REM sleep in the baseline condition. B, Effect of muscimol inhibition on EEG power for each band and each state (NRt, NREM, and REM sleep). EEG power in REM sleep is given for 3-stage scoring and 4-stage NRt scoring. For each comparison, the paired mean differences are shown in Cumming estimation plots. The raw data are plotted on the upper axes; each paired set of observations is connected by a line. Raw data are omitted in panel B. On the lower axes, each paired mean difference is plotted as a bootstrap sampling distribution. Mean differences are depicted as dots; 95% CIs are indicated by the ends of the vertical error bars. Examples of EEG traces, state-space plots, and NRt trajectories in state space are shown in Extended Data Figure 7-1.
- Figure 8.
Computer Simulations of flip-flop circuits. A, B, Configurations of the simulated flip-flop circuits. Two input scenarios are used: (A) ramping R-state drive is delivered to the flip-flop switch through the N-pool and (B) ramping R-state drive is delivered to the flip-flop switch through the R-pool. C, Connectivity matrix for one example simulation circuit. Each cell in the grid corresponds to the weight of a synaptic connection. Each row corresponds to an individual neuron as a source of connections, while every column corresponds to an individual neuron as a recipient of input. Neurons are grouped according to the pools to which they belong: input pool (n = 10), R-pool (n = 25), and N-pool (n = 25). The regions of the matrix filled with black denote the fact that there is no intrapool connectivity. Otherwise, the fill color of the cells denotes the synaptic weight between cells (white denotes a weight of zero or no connection). N→R and N→R inhibitory connections depicted are only representative examples (47 circuits were used across all simulations, where the N→R and N→R inhibitory connections were randomized). D, An example simulation run. Spike raster plots are shown for representative R-pool and N-pool input neurons (every fifth input neuron spike is shown to make visualizing the spikes easier). Spike raster plots are also shown for all N-pool and R-pool neurons. E, N-pool and R-pool raster plots as average population levels over the time course of the simulation, average spike rate difference between the pools (R-pool minus N-pool spiking), and a corresponding scoring bar, where spike rate differences are converted to one of three states: N, NRt, and R. F, G, Shows the results of every simulation across all experimental conditions. Simulation results are presented in the state-scoring format depicted in E. The procedure for setting flip-flop synaptic weights and excitatory bias currents is illustrated in Extended Data Figure 8-2. A listing of the parameter values/settings used for computer simulations is given in Extended Data Table 8-1.
- Figure 9.
Computer simulations of flip-flop circuits: analysis of bistability and switching behavior. A, Group data for NRt density originating in the R-state, calculated ratio of the number of NRt bouts over the amount of R-state, across four sets of simulations: B1 (baseline), 2 (inhibition of the R-pool), 3 (inhibition of the N-pool), and 4 (inhibition of the N-pool and R-pool). B, NRt density originating in the N-state, calculated ratio of the number of NRt bouts over the amount of N-state, for simulation sets (B1, 2, 3, and 4). C, Latency to the R-state for simulation sets (B1, 2, 3, and 4). For each comparison, the paired mean differences are shown in Cumming estimation plots. The raw data are plotted on the upper axes. On the lower axes, each paired mean difference is plotted as a bootstrap sampling distribution. Mean differences are depicted as dots; 95% CIs are indicated by the ends of the vertical error bars. D–F, The results of simulations using circuits where the ramping input was delivered through the R-pool (B5, 6, 7, and 8). G, Compares the effects from our in vivo dataset with that from simulated experiments. Effect sizes are standardized (Cohen’s d). Simulation sets (B1, 2, 3, and 4) use the circuit configuration where the ramping input is delivered to the flip-flop through the N-pool.
Extended Data
Extended Data
Code accessibility statement. The included computer code is in four parts. First, is a MATLAB script entitled “flip_flop_circuit_simulation_initializer.” This code was used to initialize simulations run with SimLIFnet (available for download at https://www.mathworks.com/matlabcentral/fileexchange/50339; copyright 2015, Zachary Danziger, all rights reserved) using the simulation parameters listed in Extended Data Table 8-1. Second is a MATLAB function entitled “forceramp,” which is required by “flip_flop_circuit_simulation_initializer” and determines the profile of the R-state promoting drive. Third, is a MATLAB script entitled “intersection_finder,” which was used to identifying all points in NREM/REM state space that bound trajectory intersections occurring within 1-min-wide windows. This procedure is needed to demarcate NREM, REM, and NRt regions of state space. Fourth, is a MATLAB script entitled “drug_diffusion_simulations,” which was used to estimate the 3-dimenional spread of drug from a point source in a microinjection versus a reverse-microdialysis scenario. This code is freely available online at https://github.com/KPGrace/Grace_Horner_Eneuro2020. Download Extended Data, ZIP file.
Extended Data Figure 2-1
Procedure for defining NREM-to-REM sleep transition dynamics. A, Flow chart outlining the EEG preprocessing steps required to construct NREM/REM state-space plots. B, C, Example state-space plots showing clusters of points corresponding to REM and NREM sleep. D, E, Procedure for defining the boundaries of the REM and NREM clusters that separate them from the intervening NRt space. This procedure identifies the position of trajectory intersections within 5-epoch spans. Example trajectory intersections are shown in D. All data points that bound all such trajectory intersections are fitted with a convex envelope to form the REM sleep and NREM sleep boundaries shown in E. F, G, Example trajectories of complete NREM-to-REM transitions (F) and the trajectories of failed transitions through NRt space (G). Download Figure 2-1, TIF file.
Extended Data Figure 7-1
Examples of normal and unstable EEG dynamics across transitions between NREM and REM sleep. A, Example spectrogram and corresponding state-space plot depicting normal spectral changes in the EEG across a NREM-to-REM sleep transition during ACSF microperfusion of the vlPAG/DpMe. B, The corresponding state-space plot for the EEG and EMG traces shown in A. The state-space trajectory moves: (i) from NREM sleep (one blue dot per epoch within NREM sleep boundary), (ii) into transitionary space (one black arrow per epoch; arrow direction indicating the direction of the state-space trajectory), (iii) and finishes within the REM sleep boundary. C, Example spectrogram and corresponding state-space plot depicting a period of unstable sleep during muscimol-mediated inhibition of the vlPAG/DpMe. D, The corresponding state-space plot for the EEG and EMG traces shown in C. The colors for the state trajectory segments correspond to the hypnogram colors in C. The trajectory begins in NREM sleep at point 1, moves into transitionary space during epoch 8, moves into REM sleep space at epoch 13, completes a transition from REM to NREM sleep space at epoch 15, moves back into transitionary space during epoch 21, re-enters NREM sleep space at epoch 30 having failed to enter REM sleep space, remains in NREM until epoch 31 before re-entering transition space and completing a transition into REM sleep space at epoch 36. Download Figure 7-1, TIF file.
Extended Data Table 8-1
Parameters used for computer simulations of flip-flop circuits. A listing of all the parameters used to produce the flip-flop circuit simulations. Download Table 8-1, DOCX file.
Extended Data Figure 8-2
Computer Simulations of flip-flop circuits: setting flip-flop synaptic weights and excitatory bias currents. A, Connection weighting was tuned prior to setting the level of excitatory bias current. Initial connection weights were divided by a factor, d, ranging from 1.8 to 2.8 in 0.1-unit increments. Nj→Ri weights were changed independent of Rj→Ni weights. A total of 121 combinations of Nj→Ri of and Rj→Ni weighting were used (Extended Data Fig. 9-1A). B–D, Examples (3/121) of the simulated combinations of flip-flop weighting. For each weighting combination, we calculated the difference in population firing rate over time and converted these data to a histogram showing the frequencies of binned R-N firing rate differences. Bimodal histograms indicate flip-flops that spontaneously switch between N-state and R-state. The height of the left and right peaks of the histograms indicate the prevalence of the N-state and R-state, respectively. The height of the intervening trough indicates the prevalence of N/R intermediate states. E, F, 11 × 11 simulation spaces where individual cells in the grid correspond to a given parameter combination and the color coding is a representation of the firing rate histogram generated from that particular set of simulations: the height of the N-peak, N/R trough, and the R-peak are indicated by the color of the left, middle, and right bars, respectively. The parameter combinations selected for experimental simulations are outlined in yellow. E, The stimulation space for synaptic weight (columns correspond to R→N weighting; rows correspond to N→R weighting). F, The simulation space for excitatory bias current (columns correspond to R neuron current; columns correspond to N neuron current). Download Figure 8-2, TIF file.
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