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Basal forebrain circuit for sleep-wake control

Nature Neuroscience volume 18, pages 1641–1647 (2015)Cite this article

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Abstract

The mammalian basal forebrain (BF) has important roles in controlling sleep and wakefulness, but the underlying neural circuit remains poorly understood. We examined the BF circuit by recording and optogenetically perturbing the activity of four genetically defined cell types across sleep-wake cycles and by comprehensively mapping their synaptic connections. Recordings from channelrhodopsin-2 (ChR2)-tagged neurons revealed that three BF cell types, cholinergic, glutamatergic and parvalbumin-positive (PV+) GABAergic neurons, were more active during wakefulness and rapid eye movement (REM) sleep (wake/REM active) than during non-REM (NREM) sleep, and activation of each cell type rapidly induced wakefulness. By contrast, activation of somatostatin-positive (SOM+) GABAergic neurons promoted NREM sleep, although only some of them were NREM active. Synaptically, the wake-promoting neurons were organized hierarchically by glutamatergic→cholinergic→PV+ neuron excitatory connections, and they all received inhibition from SOM+ neurons. Together, these findings reveal the basic organization of the BF circuit for sleep-wake control.

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Figure 1: Genetically defined BF cell types.
Figure 2: Identification of BF cell types using ChR2 tagging and optrode recording.
Figure 3: Firing rates of identified BF cell types across natural sleep-wake cycles.
Figure 4: Effects of BF neuron activation on sleep-wake states.
Figure 5: Local connectivity of BF cell types.

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Acknowledgements

We thank J. Cox, F. Weber and N. Hirai for the help with data analysis, K. Kao for technical assistance, T. Hnasko (University of California, San Diego) for sharing VGLUT2-eGFP mice, and the Stanford Neuroscience Gene Vector and Virus Core for AAV-DJ.

Author information

Author notes

  1. Min Xu and Shinjae Chung: These authors contributed equally to this work.

Authors and Affiliations

  1. Division of Neurobiology, Department of Molecular and Cell Biology, Helen Wills Neuroscience Institute, Howard Hughes Medical Institute, University of California, Berkeley, California, USA

    Min Xu, Shinjae Chung, Siyu Zhang, Peng Zhong, Chenyan Ma, Wei-Cheng Chang & Yang Dan

  2. Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, California, USA

    Brandon Weissbourd & Liqun Luo

  3. Sleep and Circadian Neurobiology Laboratory, Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, California, USA

    Noriaki Sakai & Seiji Nishino

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Contributions

M.X., S.C. and Y.D. conceived and designed the experiments. M.X. performed all of the optrode recording experiments, some of the in situ hybridization experiments and some of the slice recording experiments. S.C. performed histological characterization of BF cell types and all of the optogenetic activation experiments. S.Z. performed some of the slice experiments. P.Z. performed some of the slice recording experiments. C.M. and W.-C.C. performed some of the in situ hybridization experiments. N.S. and S.N. helped to establish sleep recording and data analysis. B.W. and L.L. provided reagents and helped to establish in situ hybridization. M.X., S.C. and Y.D. wrote the manuscript, and all of the authors helped with the revision of the manuscript.

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Correspondence to Yang Dan.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Firing rates of BF neurons in natural wake, NREM, and REM states.

a. Upper panel, firing rates of each identified cholinergic neuron in the three brain states. Each line represents data from one neuron. Lower panel, firing rates averaged across all 12 cholinergic neurons. Error bar, ± s.e.m.

b. Similar to a, for glutamatergic neurons.

c. Similar to a, for PV+ neurons.

d. Similar to a, for SOM+ neurons. Right plot, expanded view of low firing-rate range. Red lines, strongly modulated NREM-active SOM+ neurons.

e. Firing rate of an example wake-active SOM+ neuron (blue line in d). Top panel, EEG power spectrogram (0-25 Hz). Middle panel, EMG trace. Bottom panel, firing rate of the SOM+ neuron. Brain states are color coded (wake, gray; REM, orange; NREM, white).

Supplementary Figure 2 ChR2-eYFP expression in the BF induced by AAV injection and optogenetically activated neurons identified by cFos staining.

a. Fluorescence images of coronal sections at virus injection site for optogenetic activation of each BF cell type, showing location of ChR2-eYFP expression. White outlines indicate BF, including the diagonal band of Broca (NDB), magnocellular preoptic nucleus (MA), and substantia innominata (SI), based on Allen Mouse Brain Reference Atlas (http://mouse.brain-map.org/static/atlas). Inset, superposition of ChR2-eYFP (green) and cFos staining (red), shown at a higher magnification for a small region of the BF; cFos staining was performed after optogenetic activation of ChAT+, VGLUT2+, PV+, or SOM+ neurons using the same protocol as that for the experiment shown in Fig. 3. Blue dotted line indicates position of the optic fiber.

b. Number of cFos+, ChR2-eYFP+ neurons near the optic fiber tip. Error bar, ± s.e.m.

Supplementary Figure 3 Effect of laser stimulation of BF neurons on transition probability between brain states.

a. Left, probability of NREM (NR) → wake (W) state transition within each 10 s period in ChAT-Cre mice expressing ChR2 in BF. The transition probability is defined as the number of trials in which the NR → W transition occurred within the given time bin divided by the number of trials in which the animal was in NR in the previous time bin. Blue shading, period of laser stimulation (60 s, 10 Hz). Error bar, ± s.d. (bootstrap). Baseline transition probability (red line) was computed after excluding the laser stimulation period. Right, probability of W → W transition.

b. Similar to a, for VGLUT2+ neuron activation.

c. Similar to a, for PV+ neuron activation.

d. W→ NR and NR → NR transitions with SOM+ neuron activation. In all cases the probability during laser stimulation was significantly higher than the baseline (P < 10-4, bootstrap). These analyses were based on the same data shown in Fig. 4.

Supplementary Figure 4 Synaptic interactions between BF cell types measured in brain slices.

a. ChAT → VGLUT2 connections. Left, responses of an example VGLUT2+ neuron to activation of ChAT+ neurons by a single 5-ms pulse of blue light (cyan dot) and a train of 5 pulses (10 Hz). Right, responses of another VGLUT2+ neuron (same as in Fig. 5c) before (blue) and after successive blockade of GABAA receptors (brown), mAChRs (red), and nAChRs (black). These pharmacological experiments indicated that the large, prolonged inhibitory response was mediated not by GABAA receptors but by mAChRs, and the small transient excitatory response was mediated by nAChRs.

b. Diversity of ChAT → SOM connections. Left, an example SOM+ neuron exhibiting fasting spiking in response to depolarizing current injection and fast excitatory response evoked by light activation of ChAT+ neurons. Right, another SOM+ neuron with low-frequency spiking evoked by current injection and slow inhibitory response to ChAT+ neuron activation.

c. Lack of PV → ChAT input. Left, confocal image of BF slice showing presynaptic PV+ neurons expressing ChR2-mCherry (red) and postsynaptic ChAT+ neurons expressing eGFP (green). Upper right, reliable spiking of an example PV+ neuron evoked by a light pulse (5 ms) or light step (200 ms), recorded with cell-attached recording. Lower right, whole-cell recording from an example ChAT+ neuron showing many spontaneous IPSCs but no light-evoked response. The recording was made under voltage clamp at 0 mV.

Supplementary Figure 5 Unclassified brain state induced by optogenetic activation of cholinergic BF neurons.

a. Example trials in which laser stimulation induced wakefulness of ChAT-ChR2 mice. Shown are EEG power spectrum, EEG traces during selected periods (indicated by boxes), and EMG trace in each trial. Blue bar, period of laser stimulation. Note the increase in EMG activity upon laser stimulation.

b. Similar to a, but for trials in which laser stimulation induced EEG desynchronization but no change in EMG.

c. Average EEG power spectra during natural wake, NREM and REM sleep, and during laser stimulation in trials without EMG change (see examples in b). Note that the EEG power spectrum in these trials is different from any of the natural brain states, thus the brain state was left unclassified in our study. The peak at ~6 Hz (lower than the frequency of theta band observed in natural REM sleep) has also been observed in the study of Han et al.38, and in their study the brain state was classified as REM sleep.

d. Probability of wake, NREM, REM, and unclassified states before, during, and after laser stimulation, averaged across 5 ChAT-ChR2 mice (same as Fig. 4c, but including probability of unclassified state).

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–5 and Supplementary Tables 1 and 2 (PDF 1651 kb)

Supplementary Methods Checklist (PDF 387 kb)

Optrode recording from an identified BF cholinergic neuron across different brain states.

Shown are EEG power spectrogram, EMG trace, and spiking activity of the neuron, together with video recording of the ChAT-ChR2 mouse during wake, NREM and REM periods. Blue square indicates laser pulse train, which reliably evoked spiking from this neuron. The movie is shown at 4 × the original speed. (MOV 12586 kb)

Effect of optogenetic activation of glutamatergic BF neurons on brain states.

Shown are EEG power spectrogram, EMG trace, brain state, and video recording of the VGLUT2-Cre mouse (injected with Cre-inducible AAV expressing ChR2-eYFP in the BF). Laser stimulation (10 ms/pulse, 10 Hz, 30 s) during NREM (trials 1 and 2) or REM (trial 3) sleep caused immediate transitions into wakefulness. The movie is shown at 7 × the original speed. (MOV 7521 kb)

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Xu, M., Chung, S., Zhang, S. et al. Basal forebrain circuit for sleep-wake control. Nat Neurosci 18, 1641–1647 (2015). https://doi.org/10.1038/nn.4143

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