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Intrinsic dopamine and acetylcholine dynamics in the striatum of mice

Nature volume 621, pages 543–549 (2023)Cite this article

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Abstract

External rewards such as food and money are potent modifiers of behaviour1,2. Pioneering studies established that these salient sensory stimuli briefly interrupt the tonic discharge of neurons that produce the neuromodulators dopamine (DA) and acetylcholine (ACh): midbrain DA neurons (DANs) fire a burst of action potentials that broadly elevates DA in the striatum3,4 at the same time that striatal cholinergic interneurons (CINs) produce a characteristic pause in firing5,6. These phasic responses are thought to create unique, temporally limited conditions that motivate action and promote learning7,8,9,10,11. However, the dynamics of DA and ACh outside explicitly rewarded situations remain poorly understood. Here we show that extracellular DA and ACh levels fluctuate spontaneously and periodically at a frequency of approximately 2 Hz in the dorsal striatum of mice and maintain the same temporal relationship relative to one another as that evoked by reward. We show that this neuromodulatory coordination does not arise from direct interactions between DA and ACh within the striatum. Instead, we provide evidence that periodic fluctuations in striatal DA are inherited from midbrain DANs, while striatal ACh transients are driven by glutamatergic inputs, which act to locally synchronize the spiking of CINs. Together, our findings show that striatal neuromodulatory dynamics are autonomously organized by distributed extra-striatal afferents. The dominance of intrinsic rhythms in DA and ACh offers new insights for explaining how reward-associated neural dynamics emerge and how the brain motivates action and promotes learning from within.

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Fig. 1: Spontaneous periodic fluctuations in striatal DA and ACh.
Fig. 2: DA and ACh maintain a consistent temporal relationship across behavioural states.
Fig. 3: Periodic DA and ACh fluctuations are not coordinated locally in the striatum.
Fig. 4: Glutamatergic inputs synchronize CIN spiking and drive periodic ACh fluctuations.

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Data availability

The data that support the findings of this study are available from the corresponding author on reasonable request. Source data are provided with this paper.

Code availability

All code related to this study was developed in MATLAB and is available at https://github.com/ackrok/Krok-etal_2023.

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Acknowledgements

We thank G. Buzsaki, M. Long, S. Shoham, R. Tsien and members of the Tritsch laboratory for comments on the manuscript and M. Crair (Yale University) and R. Machold (NYULH) for providing the β2flox and ChATflox;Nkx2.1Cre mice, respectively. This work was supported by the National Institutes of Health (DP2NS105553 and R01MH130658 to N.X.T.; T32NS086750, T32GM007308 and T32GM136573 to A.C.K.), the Paolo and Marlene Fresco, Alfred P. Sloan, Dana, Whitehall and Feldstein Medical foundations to N.X.T. and a Vilcek Scholars Award to A.C.K. We acknowledge the New York University Langone Health Rodent Genetic Engineering Laboratory for rederivation, the Genotyping Core Laboratory for mouse genotyping, the Department of Comparative Medicine for animal care and maintenance, and the Neuroscience Institute’s imaging facilities for microscope availability. We apologize to those whose work we were unable to cite due to length limits.

Author information

Author notes

  1. These authors contributed equally: Marta Maltese, Pratik Mistry

Authors and Affiliations

  1. Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, USA

    Anne C. Krok, Marta Maltese, Pratik Mistry & Nicolas X. Tritsch

  2. Fresco Institute for Parkinson’s and Movement Disorders, New York University Langone Health, New York, NY, USA

    Anne C. Krok, Marta Maltese, Pratik Mistry & Nicolas X. Tritsch

  3. Department of Anesthesiology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China

    Xiaolei Miao

  4. State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing, China

    Xiaolei Miao & Yulong Li

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Contributions

A.C.K. and N.X.T. conceived of the project, designed and performed experiments, analysed and interpreted the data, and wrote the manuscript. A.C.K. and P.M. wrote code for photometry data acquisition and analyses, M.M. performed DA neuron lesions and helped with photometry data collection and analyses, and X.M. and Y.L. performed experiments to determine the kinetics of ACh3.0 and provided the GRAB sensors rDA1m and ACh3.0.

Corresponding author

Correspondence to Nicolas X. Tritsch.

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Competing interests

Y.L. is listed as an inventor on a patent application (PCT/CN2018/107533) describing GRAB probes. The other authors declare no competing interests.

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Extended data figures and tables

Extended Data Fig. 1 Characterization of rDA1m and ACh3.0 expression.

a, Epifluorescence images of endogenous rDA1m (left) and ACh3.0 (middle) fluorescence in a coronal section of the striatum. Right, merged image overlaid with DAPI nuclear stain (blue). Similar results were obtained in n = 16 other brains recovered for post-hoc validation of GRAB sensor expression and fiber optic placement. b, Epifluorescence images of immuno-enhanced rDA1m and ACh3.0 expressed in the dorsal striatum. Note the presence of rDA1m- and ACh3.0-positive axonal projections in the globus pallidus externus (GPe) and internus (GPi), consistent with the subcellular distribution of dopamine and muscarinic receptors in both direct and indirect-pathway SPNs. c, High magnification confocal images (single optical plane) of immuno-enhanced rDA1m and ACh3.0 in a coronal striatal section. Note the localization of both sensors to the somatic membranes of striatal neurons and throughout the neuropil, and their exclusion from corticofugal axon bundles (asterisks). Note also that some rDA1m forms intracellular aggregates. d, Same as c for a sagittal section of the substantia nigra pars reticulata. Subcellular localization of immuno-enhanced rDA1m and ACh3.0 by high magnification confocal microscopy was independently confirmed in four mice. e, Schematic showing the tip of all recovered fiber optic implants in the DLS (blue) and DMS (green) at 3 different anterior-posterior levels relative to bregma (in mm).

Extended Data Fig. 2 Kinetics of ACh3.0 sensor in the striatum in vivo.

a, Experimental preparation to optogenetically evoke ACh release in vivo using ChrimsonR while simultaneously monitoring ACh levels with ACh3.0 photometry via the same fibre optic. ChrimsonR and ACh3.0 were both virally-expressed. b, Example ACh3.0 recording (teal). ChrimsonR was stimulated every 200 s with 635 nm light flashes (20 Hz, 1 s; shown in magenta). c, detail of dashed box in b showing ChrimsonR-evoked ACh release. d, Overlay of individual ACh3.0 transients (light teal) from b aligned to optogenetic stimulation onset. Group mean shown in dark teal with overlaid exponential fits used to calculate onset (τon) and offset (τoff) time constants in black. e, ACh3.0 τon (left) and τoff (right). Mean (± s.e.m.) shown in black (τon: 138 ± 10 ms; τoff: 247 ± 32 ms; n = 12 trials from 3 mice).

Source Data

Extended Data Fig. 3 Reward-evoked DA and ACh responses in the DLS.

a, Example continuous recording of rDA1m (magenta) and ACh3.0 (teal) fluorescence, lick events (black) and treadmill acceleration (gray) illustrating the temporal dynamics of both sensors. Dashed blue lines depict uncued solenoid valve opening, which in this example did not generate large DA and ACh reward transients. b, Other reward response from same mouse. c, Example DA and ACh reward responses for a different mouse. d, Mean rDA1m (magenta) and ACh3.0 (teal) fluorescence aligned to solenoid valve opening for all uncued water deliveries followed within 1 s by consummatory licking (n = 13 mice). e, Same as d for water deliveries not followed by consummatory licking. Gray: 95% confidence interval. f, Same as d, but aligned to first lick after solenoid valve opening (i.e., first rewarded lick). g, Mean rDA1m and ACh3.0 fluorescence aligned to licks occurring between consummatory licking bouts (i.e., unrewarded licks). Gray: 95% confidence interval. h–j, Latency of first rewarded lick from solenoid valve opening (h; P = 0.52), fraction of rewards consumed within 1 s of valve opening (i; P = 0.14) and number of consummatory licks per reward delivery (j; P = 0.59) during the first (early) and last (late) quartiles of each imaging session in n = 13 mice suggest that the motivation to consume rewards is stable. k, Mean reward-aligned DA and ACh responses imaged during the first (early; gray) and last (late; colored) quartiles of each imaging session are similar in amplitude and kinetics (n = 13 mice). l, Scatterplot of the mean amplitude of reward-evoked DA peaks (left; P = 0.24) and ACh throughs (right; P = 0.74) at the beginning (early) vs. end (late) of each imaging session (n = 13 mice). m, Scatterplot of the amplitude of individual DA peaks and concurrent ACh troughs imaged during reward (blue) and periods of immobility (orange) in one example recording session. Amplitude distribution for ACh (top) and DA (right) with overlap shown in gray. n, Mean distribution of DA peak (left) and ACh trough (right) amplitudes for all mice (n = 13) normalized to the mode of reward distributions showing considerable overlap between reward and immobility states. o, Left, power spectrum of DA signal recorded in the DLS during immobility in n = 10 female mice (black) and n = 8 male mice (magenta). Right, Area under the curve of DA power spectra in the 0.5–4 Hz frequency band (P = 0.65). p, Same as o, for ACh (P = 0.84). Group means (± s.e.m.) in h–j, o and p are shown in black. Shaded regions in d–g, k, n, o and p denote s.e.m. Statistical comparisons are Student’s paired t-tests in h–j and l, and Student’s two-sample t-tests in o and p.

Source Data

Extended Data Fig. 4 Locomotion-evoked DA and ACh responses in the DLS.

a–b, Experimental setup: virally-expressed rDA1m and ACh3.0 were imaged in the DLS (a) of mice head-fixed on a transparent cylindrical treadmill (b). c, Example rDA1m and ACh3.0 fluorescence from 2 separate mice during immobility (left) and spontaneous locomotion on the treadmill (right). d, Mean standard deviation of photometry signal during immobility and locomotion for ACh3.0 (top; P = 6.5 x 10−8, Student’s paired t-test) and rDA1m (bottom; P = 3.6x10−4; Student’s paired t-test). Group mean (± s.e.m.) shown in black (n = 13 mice). e, Left, mean ACh (top) and DA (bottom) power density spectrum during locomotion (n = 13 mice). Right, Area under the curve (AUC) in 0.5–4 Hz frequency band. Group mean (± s.e.m.) shown in black. f, Heatmap of mean ACh3.0 (top) and rDA1m (bottom) fluorescence aligned to momentary peaks in treadmill acceleration during locomotion across mice. g, Group-averaged ACh3.0 (top) and rDA1m (bottom) fluorescence aligned to acceleration peaks stratified into tertiles according to acceleration magnitude. ACh and DA levels co-vary with acceleration magnitude. ACh levels peaking near acceleration maxima, whereas DA levels dip shortly before and crest shortly after acceleration maxima. h, Mean cross-correlation between treadmill acceleration and either ACh3.0 (teal) or rDA1m (magenta) fluorescence (n = 13 mice). i, Mean treadmill acceleration at different phases of periodic ACh fluctuations (dashed teal line) in the 0.5–4 Hz frequency band during locomotion (black) or immobility (gray) in n = 13 mice. During locomotion, periodic ACh fluctuations occur in phase with positive treadmill acceleration. Note that periodic ACh fluctuations during immobility are not associated with movements of the treadmill. j, Same as i for DA fluorescence. Note that DA fluctuations are phase-delayed relative to treadmill acceleration during locomotion, and not associated with micro-movements of the treadmill during immobility. Shaded regions in e, g–j denote s.e.m.

Source Data

Extended Data Fig. 5 Spontaneous fluctuations in striatal DA and ACh in unrestrained mice.

a, Simultaneous photometry recording of rDA1m (magenta) and ACh3.0 (teal) fluorescence from a mouse in an open field arena. b, Mean cross-correlation between simultaneously recorded DA and ACh during locomotion (green) and immobility (orange) in n = 4 mice. c, Peak correlation coefficient between DA and ACh (P = 0.93) during immobility and locomotion (n = 4 mice). d, Same as c for time lag of negative cross-correlation peak (p = 0.06). e, Example coherence between DA and ACh signals across frequency and time domains during a recording in an open field arena. f, Left, mean coherence between DA and ACh at different frequencies (n = 4 mice). Vertical lines depict 0.5 and 4 Hz. Right, median coherence in 0.5–4 Hz frequency band in individual mice (P = 0.25). g–h, Same as e-f for phase offset between DA and ACh (P = 0.93). i, Mean DA fluorescence at different phases of periodic DA fluctuations in the 0.5-4 Hz frequency band (n = 4 mice). j, Same as h for ACh fluorescence. k, Peak-normalized DA fluorescence vs. phase of periodic ACh fluctuations (gray dotted line) in 0.5–4 Hz frequency band during locomotion (green) and immobility (orange). Group means (± s.e.m.) in c, d, f and h shown in black. Shaded areas in b, f, h–k reflect s.e.m. All statistical comparisons are Student’s paired t-tests.

Source Data

Extended Data Fig. 6 DA and ACh levels also fluctuate periodically in DMS.

a, Experimental setup. b, Left, mean power spectrum of DA signal recorded simultaneously from DMS (magenta) and DLS (black) during immobility in n = 5 mice. Right, area under the DA power spectra in the 0.5–4 Hz frequency band in DMS and DLS. Group averages (± s.e.m.) shown in black (p = 0.8, Student’s paired t-test). c, Same as b for ACh (p = 0.3). d, Left, mean cross-correlation between DA and ACh in DMS across different behavioral states. Middle, peak correlation coefficient (Pearson’s r) in individual mice. Group averages (± s.e.m.) shown in black (**p = 0.006 vs. reward and immobility, one-way balanced ANOVA, Dunn’s multiple comparisons; n = 5 mice). Right, time lag of negative cross-correlation peak (p = 0.4, one-way balanced ANOVA). e, Magnitude of coherence between DA and ACh in DMS across frequency and time domains for an example recording. f, Left, mean coherence at different frequencies across behavioral states (n = 5 mice). Vertical lines depict 0.5 and 4 Hz. Right, median coherence in 0.5–4 Hz frequency band in individual mice. Group averages (± s.e.m.) shown in black (p = 0.09, one-way unbalanced ANOVA; n = 5 mice). g, Same as e for phase offset between DA and ACh in DMS. h, Same as f for phase offset between DA and ACh in DMS (p = 0.2, one-way unbalanced ANOVA). i, Left, mean DA fluorescence at different phase of DA fluctuations in the 0.5–4 Hz frequency band in DMS. Right, same for ACh fluorescence vs. phase of ACh fluctuations. j, Peak-normalized DA fluorescence vs. phase of ACh in DMS. k, Left, mean coherence between simultaneously recorded DADLS and AChDMS (n = 5 mice). Right, same for coherence between DADMS and AChDLS. l, Median coherence in 0.5–4 Hz band in individual mice. Group averages (± s.e.m.) shown in black (reward: DADLS+AChDMS p = 8.14 x 10−7; DADMS+AChDLS p = 6.07 x 10−7; locomotion: DADLS+AChDMS p = 7.46 x 10−5; DADMS+AChDLS p = 6.07 x 10−5; immobility: DADLS+AChDMS p = 0.004; DADMS+AChDLS p = 0.005; all vs. DADLS+AChDLS, one-way unbalanced ANOVA, Dunn’s multiple comparisons; n = 5 mice). Shaded areas in b–d, f, h–k reflect s.e.m.

Source Data

Extended Data Fig. 7 DA does not drive spontaneous fluctuations in ACh.

a, Left, example session-averaged DA fluorescence aligned to solenoid valve opening for all uncued water deliveries followed within 1 s by consummatory licking after intra-striatal infusion of saline (black) or a cocktail of D1 and D2 receptor antagonists (blue). Right, mean reward-evoked DA amplitude (n = 4 mice). b, Left, same as a for ACh. Right, scatter plot of mean reward-evoked ACh dip amplitude and timing in mice infused with saline or D1/2R antagonists (amplitude: p = 0.2; timing: p = 0.9, both vs. saline). c, Frequency (left) and amplitude (right) of spontaneous dips in ACh fluorescence during immobility (n = 4 mice). d, Same as c for peaks in ACh. e, Experimental preparation to lesion midbrain DA neurons (DANs) unilaterally while imaging DA and ACh in the DLS ipsilaterally. DANs were lesioned using either 6OHDA infusions in wild type mice (n = 7), or AAV-mediated expression of Cre-dependent caspase-3 (AAV-FLEX-taCasp3) in the midbrain DANs of DatCre mice (n = 4). f, Epifluorescence image of ACh3.0 (green) and DA transporter (DAT; red) immunofluorescence overlaid with DAPI nuclear stain (blue) in a coronal section from a DatCre mouse injected with AAV-FLEX-taCasp3 into the right midbrain. Similar results were obtained in other 10 mice. g, Example DA (magenta) and ACh (teal) fluorescence following DAN lesion during immobility. h, Left, mean ACh power spectrum during immobility before (black) and after DAN lesion (teal; n = 11 mice). Right, ACh power area under the curve (AUC) in 0.5–4 Hz frequency band. i, Same as c before and after DAN lesion (n = 11 mice). Chronic DA depletion causes phasic dips in ACh to become larger and more frequent, hinting at a negative influence of DA on ACh release. j, Same as d before and after DAN lesion (n = 11 mice). Group means (± s.e.m.) in a–d, h–j are shown in black. Shaded areas in a,b and h reflect s.e.m. All statistical comparisons are Student’s paired t-tests.

Source Data

Extended Data Fig. 8 ACh signaling is not required for periodic DA fluctuations.

a, Left, example session-averaged ACh fluorescence aligned to solenoid opening for all uncued water deliveries followed within 1 s by consummatory licking in control (black) and β2 cKODAN (blue) mice. Right, scatter plot of mean reward-evoked ACh dip amplitude and timing in control (gray; n = 13) and β2 cKODAN (blue; n = 6) mice. Group means (± s.e.m.) overlaid (amplitude: p = 0.29; timing: p = 0.89, both vs. control, Student’s two-sample t-test). b, Left, same as a for reward-evoked DA peak (amplitude: p = 0.58; timing, p = 0.33). c, Left, average coherence between DA and ACh signals in β2 cKODAN mice (n = 6) at different frequencies during reward (blue), locomotion (green) and immobility (orange). Vertical lines depict 0.5 and 4 Hz. Right, same for phase offset. d, Median DA–ACh coherence and phase in 0.5–4 Hz band in β2 cKODAN mice (n = 6) normalized to control mice across conditions (coherence: reward p = 0.9, locomotion p = 0.3, immobility p = 0.9; phase: reward p = 0.4, locomotion p = 0.6, immobility p = 0.2; all comparisons vs. control, Student’s two-sample t-test). Group mean (± s.e.m.) shown in black. e, Left, average DA fluorescence at different phases of periodic DA fluctuations in the 0.5–4 Hz frequency band across behavioral states in β2 cKODAN mice (n = 6 mice). Right, same for ACh fluorescence vs. phase of periodic ACh fluctuations. f, Experimental preparation for local pharmacological inhibition of nAChR signaling. g, Same as a after DLS infusion of saline (black) or the nAChR antagonist DHβE (blue; amplitude: p = 0.4; timing: p = 0.13, both vs. saline, Student’s paired t-test, n = 5 mice). h, Same as g for DA (amplitude: p = 0.9; timing: p = 0.15). i, Example DA (magenta) and ACh (teal) traces during infusion of DHβE. j, Left, mean ACh power spectrum during immobility following intra-striatal infusion of saline (black) or DHβE (blue; n = 8 mice). Right, ACh power area under the curve (AUC) in 0.5–4 Hz frequency band (p = 0.6, Student’s paired t-test). k, Same as d for Pearson’s correlation coefficient r (reward: p = 0.2, locomotion: p = 0.5, immobility: p = 0.06), coherence (reward: p = 0.04, locomotion: p = 0.6, immobility: p = 0.09) and phase (reward: p = 0.2, locomotion: p = 0.5, immobility: p = 0.6) in DHβE normalized to saline (all comparisons vs. saline, Student’s paired t-test; n = 8 mice). l, Experimental preparation for local pharmacological inhibition of mAChR signaling in the DLS. m, Left, same as g following infusion of saline (black) or the mAChR antagonist scopolamine (blue). Right, amplitude of reward-evoked dip in ACh fluorescence (p = 0.02; n = 5 mice). n, same as j after infusion of saline or mAChR antagonist (p = 2.5 x 10−4, Student’s paired t-test; n = 5 mice). This effect confirms that scopolamine reaches the volume of tissue imaged by the fiber optic. o, Same as m for DA (amplitude: p = 0.6, timing: p = 0.09; n = 5 mice). p, Same as n for DA (p = 0.048). This effect is consistent with the role of facilitatory effects of presynaptic mAChRs on DAN axons (see ref. 31). Shaded areas in a,b,c,e,g,h,j and m–p reflect s.e.m.

Source Data

Extended Data Fig. 9 Midbrain DAN activity underlies periodic fluctuations in striatal DA.

a, Experimental preparation for simultaneously imaging the activity of DANs in the SNc and their axons in the DLS. b, Example photometry recording of GCaMP6f in the SNc (black) and DLS (blue) during immobility. c, Left, average (± s.e.m. shown as shaded region) cross-correlation between SNc and DLS signals during immobility in n = 6 mice. 95% confidence interval shown in gray. Right, peak correlation coefficient between SNc and DLS signals. Group mean (± s.e.m.) in black. d, Experimental preparation for pharmacological silencing of SNc while imaging of rDA1m and ACh3.0 in the DLS. e, Left, Example continuous recording of ACh3.0 (teal) and rDA1m (magenta). Black line depicts muscimol infusion. Right, Detail of dashed boxes showing ACh and DA fluctuations during immobility before (e1) and following (e2) infusion of muscimol. Note that muscimol abolishes phasic DA transients as well as ‘global’ DA levels in the DLS, whereas ACh global levels and phasic transients persist. f, Average global ACh and DA fluorescence during immobility after infusion of saline and muscimol. Group mean (± s.e.m.) shown in black (ACh: p = 0.021; DA: p = 0.0001, Student’s paired t-test; n = 6 mice). g, Frequency (left) and amplitude (right) of spontaneous dips in ACh fluorescence recorded during immobility after infusion of saline (gray) or muscimol (teal). Group mean (± s.e.m.) shown in black (n = 6 mice). p-values (Student’s paired t-tests) indicated in figure. h, Same as g for peaks in ACh fluorescence. Collectively, these data confirm that spontaneous DA fluctuations in the DLS are driven by the somatic activity of midbrain DANs, whereas spontaneous ACh transients do not require DAN activity. i, Experimental preparation for local pharmacological inhibition of neurotransmitter receptors in the DLS. j, Average global ACh fluorescence measured during immobility after intra-striatal infusion of saline, the mAChR antagonist scopolamine (p = 6.9 x 10−6; n = 5 mice), the D1/2R antagonists SCH23390 and sulpiride (p = 0.24; n = 4 mice) or the iGluR antagonists NBQX and APV (p = 0.41; n = 8 mice; all comparisons are Student’s paired t-test vs. saline control). Data are expressed as a fraction of global ACh fluorescence pre-infusion. Group means (± s.e.m.) are shown in black. Note that mAChR antagonist blocks ACh3.0 (and therefore serves a positive control for maximal possible change in ACh signal) and that blocking iGluRs in the DLS does not significantly alter overall ACh3.0 fluorescence compared to saline, suggesting that CINs continue to release ACh via spontaneous, cell-autonomous firing. k, Same as l for global DA fluorescence after infusion of saline, scopolamine (p = 0.24), D1/2R antagonists (p = 1.1 x 10−4) or iGluR antagonists (p = 0.53). Note that blocking iGluRs in the DLS does not alter overall rDA1m fluorescence either, suggesting that DA axons continue to release DA.

Source Data

Extended Data Fig. 10 Characterization of electrophysiological recordings in the DLS.

a, Experimental preparation for acute in vivo extracellular recordings in the DLS. b, Scatter plot of spike properties used to distinguish units as putative SPNs (pSPNs; gray), putative CINs (pCINs; blue), or other putative interneurons (green). c, Average waveform (left) and auto-correlograms (right) for pSPNs (black), pCINs (blue), and other neurons (green). d–g, Distribution of firing rates (d), coefficient of variation of inter-spike intervals (e), phasic activity index (f), and waveform duration for pSPNs (black), pCINs (blue), and other neurons (green). h, Mean (± s.e.m.) pCIN-pCIN cross correlogram (CCG) computed from all units shown in Fig. 4c (n = 157 pairs). 95% confidence interval shown in gray. i, Proportion of CCGs from Fig. 4c with firing rates above or below the 95% confidence interval (bin size: 20 ms). j, Left, experimental preparation for simultaneous ACh photometry and acute in vivo extracellular recordings from the DLS. Right, location of all recovered fiber optic implant tips (blue) and electrode tracks (red) in the DLS merged across anterior-posterior levels +0.5 to 0.75 mm relative to bregma. k, Men firing rate of two simultaneously recorded pCIN units aligned to ACh fluorescence peaks during immobility. l, Instantaneous (mean normalized) firing rate of pCINs (n = 22) aligned to ACh fluorescence peaks during immobility. Dots indicate units shown in k. m, Average firing rate (normalized to mean; ± s.e.m. shown in shaded region) of all pCINs shown in l. 95% confidence interval shown in gray. n–p, Same as k–m aligned to ACh fluorescence troughs.

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Krok, A.C., Maltese, M., Mistry, P. et al. Intrinsic dopamine and acetylcholine dynamics in the striatum of mice. Nature 621, 543–549 (2023). https://doi.org/10.1038/s41586-023-05995-9

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