Distinct modes of dopamine modulation on striatopallidal synaptic transmission

Domain: biology
Published: 2026-04-03
Editorial outcome: major_revision

Abstract
Dopamine affects voluntary movement by modulating basal ganglia function. However, the
contribution of dopamine on striatopallidal synapses, an initial hub in the indirect pathway
connecting the striatum to the GPe, remains poorly understood because of the sparse dopaminergic
innervation. Here, we combine optogenetic projection targeting, whole cell patch clamp recordings
in acute brain slices from mice, and computational modeling to overcome this limitation. We show
that dopamine activates D2 receptors (D2Rs) and D4 receptors (D4Rs) differentially in distinct
GPe subregions. In a pinwheel-like fashion, dorsolateral and ventromedial GPe expresses high
levels of D2Rs, which exert presynaptic inhibition, while in dorsomedial and ventrolateral GPe
D4Rs cause postsynaptic inhibition. Dopamine depletion by 6-OHDA reshapes the region-specific
effect of dopamine, shifting it in the opposite direction and contributing to hypokinesia. These
findings reveal the mechanism by which the different modality information conveyed spatially
through the indirect pathway is differentially modulated by dopamine at striatopallidal synapses.

Introduction
The proper control of voluntary movement is vital for survival. The core brain regions modulating
voluntary movement are the basal ganglia, a network of interconnected subcortical nuclei1,2.
Sensory and motor information, widely distributed across the cortex, enters the basal ganglia,
which contributes, among other functions, to select the appropriate motor strategy3. Central among
these processes is the modulation of neuronal activity and synaptic transmission by the
neuromodulator dopamine (DA) within the basal ganglia. The primary source of DA for goal-
directed movement is the midbrain DA neurons located in the substantia nigra pars compacta (SNc),
which predominantly innervate the striatum via the nigrostriatal pathway4. Within the striatum, the
input nucleus of the basal ganglia, over 90% of neurons are GABAergic projection neurons known
as medium spiny neurons (MSNs)5. Anatomically, the striatal MSNs can be categorized into two
distinct groups: “direct” and “indirect” pathway MSNs. Interestingly, direct MSNs (dMSNs)
projecting “directly” to the SNr/GPi (substantia nigra pars reticulata and internal globus pallidus,
respectively), the primary output nuclei of the basal ganglia, express the DA D1 receptors (D1Rs),
while indirect MSNs (iMSNs) projecting “indirectly” to the SNr/GPi by way of the external globus
pallidus (GPe), express the DA D2 receptors (D2Rs)1,2. DA orchestrates the activity of MSNs
through these receptors and the ensuing synaptic plasticity of excitatory afferents. In an action
selection model, the direct pathway promotes appropriate motor strategies, whereas the indirect
pathway suppresses other competing or inappropriate ones3,4. Consequently, the depletion of DA
causes hyperactivity of the indirect pathway, resulting in an excessive inhibition of the thalamus
and ultimately leading to the suppression of movement5–7.

Striatopallidal synapses in the GPe, the first synaptic connection between nuclei of the
indirect pathway, are a critical node where the axon terminals of extensively distributed iMSNs
converge. Midbrain dopaminergic neurons, while predominantly projecting to the striatum, also
give rise to collateral axons innervating the GPe6,7. However, studies to date have found only
limited evidence supporting the functional significance of this innervation in modulating
striatopallidal synaptic transmission6,8–10. On the other hand, it has been reported that the
administration of DA or D2R agonists reduces striatopallidal GABAergic transmission with
increased paired-pulse ratio (PPR), possibly attributable to the presence of presynaptic D2Rs at
striatopallidal axon terminals8–10. In addition, GPe neurons seem to express other D2-like receptors,
including D4Rs11,12, which may contribute to DA's postsynaptic effect at striatopallidal synapses13.
Despite these findings, our understanding of the dopaminergic modulation of striatopallidal
transmission in the GPe is still incomplete. Notably, midbrain DA neurons are not a monolith; they
encompass molecularly and functionally heterogeneous populations that can innervate
anatomically and spatially distinct compartments of the striatum and other basal ganglia nuclei.
This characteristic of DA neurons and their axons may explain in part the fact that each subdivision
of the striatum is involved in specific animal behaviors12,13. In a similar vein, recent findings
suggest that the indirect pathway can maintain anatomically parallel subnetworks, and
striatopallidal synapses, depending on their anatomical location within the GPe, may convey
different modalities of information14,15. However, the majority of previous studies on the GPe have
treated striatopallidal synapses as uniform in their physiological properties. Hence, whether
dopaminergic modulation of synaptic transmission can vary by the anatomical location of
striatopallidal synapses in the GPe remains to be elucidated.

Here, we sought to determine how dopaminergic modulation shapes striatopallidal
synaptic transmission in the GPe. Our data demonstrated that dopaminergic axons originating from
the midbrain innervate the GPe, exhibit region-specific distribution, and locally release dopamine.
In addition, DA D2-like receptors could modulate striatopallidal synaptic transmission in a region-
specific manner across different subdivisions of the GPe. Specifically, the activation of D2-like
receptors resulted in an increased paired-pulse ratio (PPR) and a decrease in GABAergic
transmission within the dorsolateral (DL) and ventromedial (VM) regions of the GPe. Surprisingly,
this dopaminergic effect on PPR was absent in the ventrolateral (VL) and dorsomedial (DM) GPe,
despite the observed reduction in GABAergic transmission in these areas.

In contrast, DA depletion reshaped the modulation of striatopallidal transmission by DA
D2-like receptors in the GPe. 6-OHDA-induced DA depletion particularly promoted an increase
in PPR in the VL and DM subregions of the GPe, while attenuating the rise in PPR in the DL and
VM GPe. These results suggest that distinct sensory-motor information conveyed via the indirect
pathway can be differentially modulated by DA, contingent upon the anatomical locations of
striatopallidal synapses. Given that the structural and functional organization of basal ganglia
circuits determines DA-related psychomotor functions and behaviors, our findings offer insights
into the previously overlooked role of dopaminergic modulation on striatopallidal synapses and
globus pallidus in health and disease.

Results
DA axons capable of releasing DA innervate the GPe with regional heterogeneity
Although dopaminergic innervation of the GPe has been reported previously6,7, direct evidence
supporting local dopamine release from these axon terminals remains limited. We first examined
the origin of dopaminergic axons innervating the GPe and found that the majority of TH-positive
axons originated from SNc DA neurons16,17 (Supplementary Fig. 1). Attempts to monitor DA
transmission in the GPe using conventional electrochemical methods have been hindered by the
sparse innervation of dopaminergic axon fibers to the GPe. However, recent advancements in
fluorescent reporters for DA hold great promise for examining relatively weak DA transmission in
brain regions such as the GPe8,18,19. To investigate whether dopaminergic axonal boutons
innervating the GPe are functional and capable of releasing DA, we employed adeno-associated
viruses (AAVs) encoding the genetically encoded fluorescent DA sensor GRAB (rDA2h)20.
These AAVs were injected into the GPe, and DA release was monitored by changes in fluorescence
intensity within the imaging area. To compare the relative amplitude of DA transmission across
other DA-projecting regions, AAVs expressing the GRAB sensor were also injected into the M1
cortex and dorsolateral striatum (DLS). Three weeks post-injection, acute brain slices were
prepared, and one-photon imaging combined with electrical stimulation was utilized to measure
stimulus-evoked DA release. Although relatively small in amplitude compared to the DLS,
electrical stimulation clearly evoked DA transmission in the GPe, indicating that DA axonal
boutons in the GPe are functional and release DA (Fig. 1a,b). Consistently, fast-scan cyclic
voltammetry (FSCV) measurements detected reliable evoked DA release in both the DLS (373.27
± 40.15 nM) and GPe (14.27 ± 3.41 nM), confirming that dopaminergic terminals in the GPe are
capable of releasing measurable amounts of DA (Supplementary Fig. 2a-c).

To further interrogate the innervation patterns of DA axons within the GPe subregions, we
analyzed the regional variations of DA fibers by dividing the GPe into four subregions along the
dorsoventral and lateromedial axes (Fig. 1c). We selectively expressed tdTomato in iMSNs by
crossing Adora2A-Cre mice with Ai9 mice to visualize striatopallidal axon fibers. We quantified
both striatopallidal and dopaminergic axonal areas in the GPe through double-immunostaining for
tyrosine hydroxylase (TH) and tdTomato (RFP). The regional expression of tdTomato in Adora2A-
Cre;Ai9 mice was consistent across the different subregions of the GPe (Fig. 1d). Interestingly,
although TH-positive DA fibers are comparable within the striatal regions21, TH-positive DA
axons innervated the GPe with significant spatial heterogeneity; DA fibers are more abundant in
the medial and ventral parts of the GPe compared to the lateral and dorsal regions (Fig. 1e,f). To
determine whether this anatomical heterogeneity translates into functional differences in DA
transmission, we measured stimulus-evoked DA release across GPe subregions using GRAB
DA
imaging and FSCV. Both approaches detected reliable DA signals throughout the GPe, although
regional variation was not clearly observed (Fig. 1g-i and Supplementary Fig. 2d-f).

DA D2-like receptors modulate striatopallidal transmission through distinct mechanisms
within the subregions of the GPe
The bath application of either DA or D2-like receptors agonist quinpirole in the GPe has been
documented to reduce GABAergic transmission at striatopallidal synapses while simultaneously
increasing the paired pulse ratio (PPR)10,22,23. These findings indicate a presynaptic action of DA
through D2Rs at striatopallidal axon terminals originating from iMSNs. We first revisited the
functional role of striatopallidal presynaptic D2Rs on GABAergic synaptic transmission by
measuring the PPR to indirectly monitor release probability24,25. Most of the previous studies
examining striatopallidal synapses have utilized electrical stimulation to evoke striatopallidal
synaptic transmission. However, this approach is inherently prone to the unintended activation of
other axons including collaterals from dMSNs axons, pallidostriatal axons, and GPe collateral
axons26–28. To avoid this possibility, we employed optogenetic techniques to selectively stimulate
striatopallidal axons26,27. Specifically, we expressed channelrhodopsin-2 (ChR2) in iMSNs by
crossing Adora2A-Cre mice with transgenic mice harboring a conditional floxed allele of ChR2 in
the Rosa26 locus (Ai32 mice) (Fig. 2a). First, we validated the stable maintenance of oIPSC
(optically evoked inhibitory postsynaptic current) baselines over a 40-minute period and reliably
observed paired-pulse responses at a 50 ms inter-stimulus interval under our recording conditions,
in agreement with previous studies using comparable protocols29–31 (Supplementary Fig. 3a,b).
Consistent with previous reports using electrical stimulation22,23, the application of quinpirole
significantly reduced the light-evoked GABAergic transmission (oIPSCs) and increased the PPR
at striatopallidal synapses (Fig. 2b,c and Supplementary Fig. 3c,d). Although differences in the
oIPSC kinetics of striatopallidal synaptic transmission were observed depending on the
postsynaptic GPe neuronal types (Table S1), the response to DA D2-like receptor activation did
not differ between GPe neuronal types, consistent with previous studies22.

As mentioned above, most prior studies have assumed that striatopallidal synapses in the
GPe possess homogeneous physiological characteristics. Given the observed heterogeneity in
dopaminergic innervation across the GPe (Fig. 1c-f), we next investigated whether D2-like
receptors modulate striatopallidal synaptic transmission in a region-dependent manner. To this end,
we divided the GPe into four quadrants along the dorsoventral and mediolateral axes, guided by
the distribution pattern of TH-positive fibers, providing an operational framework for subregional
analysis (Fig. 2e-h). To minimize ambiguity arising from anatomical boundaries, we avoided
recording neurons near quadrant overlaps. Most importantly, we observed that the effect of
quinpirole at striatopallidal synapses exhibited significant variation dependent on the specific
subregions of the GPe. While quinpirole universally suppressed GABAergic transmission across
all subregions of the GPe, it induced distinct alterations in the PPR. Quinpirole treatment increased
the PPR in the dorsolateral (DL) and ventromedial (VM) subregions, whereas no significant
change in PPR was observed in the ventrolateral (VL) and dorsomedial (DM) subregions of the
GPe (Fig. 2e-h and Supplementary Fig. 3e-h). When directly comparing these subgroup pairs, the
quinpirole-induced PPR increase was significantly greater in the DL and VM GPe than in the VL
and DM GPe, suggesting region-specific modulation within the GPe (Fig. 2d). To further confirm
both the robustness and the reversibility of this subregional pattern, we performed additional
experiments using a lower concentration of quinpirole (20 nM). As with the 10 µM condition,
quinpirole increased the PPR in the DL and VM but not in the VL and DM. Notably, both oIPSC
amplitude and PPR fully recovered to baseline after wash-out (Supplementary Fig. 4,5), indicating
that the observed modulation represents a reversible D2R-mediated effect rather than a time-
dependent rundown. Consistent results were also obtained in adult mice using 20 nM DA
application, confirming the reproducibility of this subregional pattern (Supplementary Fig. 6).

In light of the regional heterogeneity observed in dopaminergic modulation within the
GPe, we hypothesized the presence of an underlying anatomical factor that might partially account
for this variation. To explore this, we quantified the nearest neighbor distances between putatively
functional DA boutons and striatopallidal synapses. Utilizing Adora2A-Cre;Ai9 mice, we
performed multi-color immunostaining coupled with enhanced confocal microscopy. The co-
localization of the presynaptic protein Bassoon and TH was considered as functional DA
boutons32,33. Furthermore, striatopallidal GABAergic synapses were identified by the co-
localization of presynaptic RFP and postsynaptic GABA R (Supplementary Fig. 7a,b).
Interestingly, the DL and VM regions of the GPe, which exhibited elevated PPR in response to
quinpirole, displayed shorter nearest neighbor distances between functional DA boutons and
striatopallidal GABAergic synapses compared to the VL and DM GPe (Supplementary Fig. 7c-g).
This anatomical characteristics within the GPe may also have functional implications for the
region-dependent variability in dopaminergic modulation of striatopallidal transmission.

Region-specific dopaminergic modulation of striatopallidal synaptic transmission in the GPe
is driven by differential contributions of presynaptic D2Rs and postsynaptic D4Rs
To determine how the activation of D2-like receptors differently modulates striatopallidal
transmission across various subregions of the GPe, we compared the quantal properties of
striatopallidal GABAergic transmission before and after treatment with quinpirole34,35. For quantal
analysis, Ca2+ was substituted with Sr2+ in the bath solution to facilitate asynchronous release.
Striatopallidal GABAergic transmission in some GPe neurons did not respond to Sr2+ treatment;
consequently, these cells were excluded from the quantal analysis. It is noteworthy that neurons in
the lateral GPe regions (DL, VL) exhibited a lower propensity for evoking asynchronous release.
When Sr2+ was applied, no significant differences were observed in the quantal amplitude and
frequency of oIPSCs among the GPe subregions. Following quinpirole treatment with Sr2+
replacement, a reduction in quantal amplitude was observed across all GPe subregions (Fig. 3a-d).
However, a decrease in quantal frequency was specifically found in the DL and VM GPe
subregions (Fig. 3a,d,e), where an elevation in PPR by quinpirole was also detected. Direct
subgroup comparison further showed that the reduction in quantal frequency was significantly
greater in the DL and VM GPe than in the VL and DM GPe (Fig. 3f). These findings suggest that
the activation of postsynaptic D2-like receptors in the GPe universally suppresses GABAergic
transmission across all subregions, while presynaptic D2-like receptors in the DL and VM GPe
modulate GABA release.

To explore potential regional variations in the quantal kinetics of striatopallidal synaptic
transmission in the GPe, we conducted a clustering analysis on Sr2+-induced quantal responses.
This analysis aimed to determine whether specific quantal characteristics varied across the DL,
VL, DM, and VM regions of the GPe. Each quantal response was characterized by amplitude, rise
time, and decay constant, standardized across cells, and subjected directly to a recursive k-means
clustering procedure. This analysis yielded 27 stable clusters across all responses (Supplementary
Fig. 8a). Comparison of these categories across the GPe subregions revealed a notable divergence
in the VM region. Unlike the DL, VL, and DM regions, which shared similar quantal
characteristics, the VM region exhibited unique quantal categories with significantly different
kinetics (Supplementary Fig. 8b-e and Table S2). This distinct pattern may indicate that
striatopallidal synapses in the VM region of the GPe may originate from functionally different
sources in the striatum or employ a unique set of presynaptic mechanisms, potentially reflecting
functional specialization within the GPe circuitry. As a further investigation into the synaptic
vesicle release machinery, we examined the individual isoforms of synaptotagmin at striatopallidal
axon terminals to determine potential subregional variations in the presynaptic fusion machinery
within the GPe (Supplementary Fig. 9a,d,g). Our findings showed that striatopallidal terminals are
predominantly co-localized with synaptotagmin 1 across all GPe subregions (Supplementary Fig.
9j,k). Synaptotagmin 7 exhibited slightly higher expression in the medial and dorsal regions
relative to the lateral and ventral regions of the GPe (Supplementary Fig. 9e,f), while
synaptotagmin 5/9 was preferentially localized in the dorsal GPe compared to the ventral GPe
(Supplementary Fig. 9h,i). These observations implicate subregion-specific heterogeneity of
striatopallidal synapses in basal synaptic features including quantal characteristics and synaptic
release machinery. While these differences in quantal kinetics and synaptotagmin expression do
not directly explain the observed DA modulation, they support the notion that striatopallidal
synapses exhibit subregion-specific molecular and physiological heterogeneity.

We next focused on identifying D2-like receptors at presynaptic and postsynaptic sites of
striatopallidal synapses across the different GPe subregions. GPe neurons in rodents are reported
to express DA D4 receptors (D4Rs)11,12, yet there are conflicting studies regarding the postsynaptic
dopaminergic effects on striatopallidal synaptic transmission13,22,23. We pharmacologically
evaluated the postsynaptic effect of D4Rs on striatopallidal transmission using optogenetic
stimulation combined with a highly selective D4R agonist A-412997 (2-(3′,4′,5′,6′-tetrahydro-2′H-
[2,4′] bipyridinyl-1′-yl)-N-m-tolyl-acetamide). If GABAergic transmission at striatopallidal
synapses is suppressed by postsynaptic D4Rs, treatment with a selective D4R agonist A-412997
would result in an attenuation of oIPSCs without altering the PPR. Consistent with our quantal
analysis of striatopallidal transmission, treatment with A-412997 led to a widespread reduction in
oIPSCs across all GPe subregions, without affecting the PPR (Supplementary Fig. 10 and
Supplementary Fig. 11c-f). This finding suggests that postsynaptic D4Rs inhibit GABAergic
transmission uniformly throughout the GPe. To clearly validate the region-specific role of
presynaptic D2Rs in regulating GABA release at striatopallidal synapses, we assessed the effects
of quinpirole on oIPSCs and PPR under continuous bath application of the D2R-selective
antagonist L-741626. We found that quinpirole continued to decrease GABAergic transmission in
the presence of L-741626 application; however, the previously observed increase in PPR induced
by quinpirole was no longer present in the DL and VM GPe regions (Fig. 3g-j and Supplementary
Fig. 11a,b). These two complementary pharmacological approaches together indicate that
postsynaptic inhibition is uniformly mediated by D4Rs, whereas regionally distinct presynaptic
modulation is driven by presynaptic D2Rs.

We next questioned whether differences in the localization and spatial distribution of
D2Rs at striatopallidal axon terminals might contribute, at least in part, to the region-specific
dopaminergic modulation of synaptic transmission in the GPe. To selectively label striatopallidal
axons and synaptic terminals, we injected a Cre-inducible adeno-associated virus (AAV)
expressing both mGFP and synaptophysin-mRuby into the entire striatum of Adora2A-Cre mice
(Fig. 4a,b). Subsequently, we performed multi-color immunostaining and enhanced confocal
imaging to quantify the spatial localization of D2Rs at striatopallidal axon terminals (RFP+) or
axons (GFP+) within each GPe subregion (Fig. 4c). Our results revealed that the DL and VM GPe
subregions exhibited a higher degree of co-localization of D2Rs on striatopallidal axons (D2R+
GFP+) and axon terminals (D2R+ RFP+) compared to the VL and DM GPe subregions (Fig. 4d
and Supplementary Fig. 12a). Additionally, the nearest neighbor distance between D2Rs on
striatopallidal axons or axon terminals was shorter in the DL and VM GPe compared to the VL
and DM GPe (Fig. 4e). We also investigated the expression of D4Rs and GABA Rs on
postsynaptic neurons in the GPe. In Adora2A-Cre;Ai9 mice, striatopallidal axons were labeled
with RFP and GABA Rs were immunostained to mark the dendrites of GPe neurons (Fig. 4f,g).
Using multi-color immunostaining and 3D reconstruction, we were able to clearly identify the
separation between striatopallidal axons (RFP+) and postsynaptic neuronal dendrites labeled with
GABA R in the GPe (Fig. 4h). We found that both the volume and number of D4R-positive signals
were significantly greater in the VL and DM GPe subregions compared to the DL and VM GPe,
whereas no significant differences were observed in the volume and number of GABA R-positive
signals (Fig. 4i,j and Supplementary Fig. 12b,c). Furthermore, the nearest neighbor distances
between D4Rs and GABA Rs were markedly shorter in the VL and DM GPe compared to the DL
and VM GPe (Fig. 4k). These findings suggest that region-specific differences in the expression,
localization, and spatial distribution of presynaptic D2Rs and postsynaptic D4Rs may partially
underly the distinct dopaminergic modulation of striatopallidal transmission observed across GPe
subregions.

Pre- and postsynaptic DA receptors fine-tune ongoing activity in the GPe through region-
specific modulations
Information spanning a wide range of frequencies, from low to high, propagates through the basal
ganglia circuits including the indirect pathway. To further explore the functional implications of
region-specific dopaminergic modulations on striatopallidal transmission, beyond their effects on
PPR, we investigated how DA receptor activation influences ongoing activity at striatopallidal
synapses. We optogenetically stimulated striatopallidal axon terminals with trains of 10 light
pulses at 20 Hz, and compared the inhibitory postsynaptic responses across the GPe subregions29.
We found that postsynaptic responses to 10-pulse stimulation varied significantly depending on
the anatomical location within the GPe (Fig. 5a,d,g,j). High-frequency stimulation often leads to
short-term depression at synapses, primarily due to the depletion of the readily releasable pool
(RRP)36. In the GPe, such stimulation induced pronounced short-term depression in the DL and
VL subregions, with GABAergic transmission significantly suppressed throughout the stimulation
trains (Fig. 5a-f). In contrast, in the VM GPe, oIPSCs were initially facilitated but ultimately
transitioned to synaptic depression (Fig. 5j-l). Notably, striatopallidal synapses in the DM GPe
consistently exhibited short-term facilitation, underscoring the heterogeneity of synaptic
modulation across GPe subregions (Fig. 5g-i,m).

Upon application of quinpirole at striatopallidal synapses, GABAergic transmission
during 10-pulse stimulation was significantly inhibited by DA receptor activation in the DL and
VM GPe. However, presynaptic mechanisms partially counteracted this inhibition, sustaining
short-term facilitation to mitigate frequency-dependent suppression (Fig. 5b,c,k,l,n). In contrast,
oIPSCs were consistently suppressed by high-frequency stimulation in the VL GPe, where
GABAergic transmission had previously been diminished by quinpirole without any change in the
PPR. To assess the difference between the initial and final responses elicited by the 20 Hz
stimulation, the ratio of the oIPSC amplitude for the tenth stimulus (P10) to that of the first stimulus
(P1) was calculated. The lack of change in the P10/P1 ratio following quinpirole treatment suggests
that DA receptor activation in the VL GPe affects striatopallidal transmission exclusively through
gain modulation (Fig. 5e,f). Similarly, in the dorsomedial (DM) GPe, quinpirole attenuated
GABAergic transmission, and the P10/P1 ratio remained unchanged, further indicating gain
modulation. Despite this, striatopallidal synapses in the DM GPe sustained synaptic transmission
by maintaining short-term facilitation, thereby functioning as a high-pass filter independent of DA
receptor activation (Fig. 5h,i). Additionally, the charge ratio, which quantifies the relative
suppression of trains of oIPSCs normalized to the suppression of single oIPSC29, differed between
the DL-VM GPe and VL-DM GPe (Fig. 5n). These findings collectively suggest that ongoing
activity at striatopallidal synapses is differentially shaped based on the anatomical location within
the GPe. Moreover, while GABAergic transmission at striatopallidal synapses is universally
suppressed by DA receptor activation throughout the GPe, pre- and postsynaptic DA receptors
fine-tune this transmission in a region-specific manner.

Dopaminergic axons are differentially denervated by 6-OHDA across the GPe subregions
Given that the dopaminergic projections from the SNc primarily follow the nigrostriatal pathway,
which predominantly innervates the striatum, the degeneration of TH-positive dopaminergic axons,
a key pathological hallmark of Parkinson’s disease (PD), has been extensively characterized within
the striatum. However, several studies have also reported pathological alterations in dopaminergic
innervation of the GPe in both human patients and animal models37–39. This led us to investigate
whether the degeneration of dopaminergic axons in animal models of DA depletion exhibits
regional heterogeneity within the GPe. To investigate whether dopaminergic axons in the GPe are
themselves heterogeneous across subregions, and whether such heterogeneity might provide a
cellular and anatomical basis for region-specific dopaminergic modulation, we examined the
spatiotemporal pattern of axonal degeneration following DA depletion. To induce DA depletion
pharmacologically, we unilaterally infused 6-hydroxydopamine (6-OHDA) into the medial
forebrain bundle (MFB) of Adora2A-Cre;Ai9 mice (Supplementary Fig. 13a). We then examined
the time-dependent denervation of DA axons in the GPe subregions at 1, 3, and 5 days post-6-
OHDA administration using double immunostaining for TH and RFP (Supplementary Fig. 13b).
Because this model does not fully recapitulate the progressive pathology of Parkinson’s disease,
we hereafter refer to it as a DA depletion model. Under these conditions, DA axons were
significantly diminished in the DLS, the primary projection target of SNc DA neurons, as early as
one day after the 6-OHDA injection (Supplementary Fig. 13c,f,g). As depicted in Figure 1, the
heterogeneity in DA axonal innervation across GPe subregions was also preserved in the
contralateral hemisphere, and TH-positive axonal loss relative to the contralateral side varied
across GPe subregions and time points (Supplementary Fig. 13d,e). Notably, the degeneration of
DA axons in the DL, VL, and VM regions of the GPe, similar to the DLS, was observed as early
as one day post-6-OHDA injection. In contrast, DA axons in the DM GPe remained relatively
intact at Day 1, whereas the DL GPe showed the mildest reduction at Day 5 (Supplementary Fig.
13d,e). Collectively, these findings suggest that DA axons in distinct GPe subregions display
differential temporal susceptibility to degeneration following DA depletion.

DA depletion reorganizes region-specific dopaminergic modulation of striatopallidal
synaptic transmission
Studies in both nonhuman primates and humans have demonstrated increased oscillatory
synchronization in the GPe of Parkinsonian models and PD patients40,41. In addition, several
studies in rodent models suggest that the heightened striatopallidal GABAergic inhibition of the
GPe under DA-depleted conditions may contribute to the pathophysiological changes observed in
the GPe10,42. We sought to determine whether dopaminergic modulation of striatopallidal
transmission in the GPe is also altered in a region-specific manner under DA-depleted conditions.
To unravel the physiological changes in striatopallidal transmission under DA-depleted conditions,
we unilaterally injected 6-OHDA into the MFB of Adora2A-Cre;Ai32 mice (Fig. 6a). To capture
early-stage synaptic adaptations to DA loss, we conducted electrophysiological recordings at 3
days post-6-OHDA infusion. Three days post-6-OHDA infusion, we bath-applied quinpirole and
measured oIPSCs and PPR changes across different GPe subregions (Fig. 6b-e). In the
contralateral hemispheres, we replicated the region-specific dopaminergic modulation of
striatopallidal synaptic transmission; oIPSCs decreased with an increased PPR in the DL and VM
GPe, whereas oIPSCs were reduced without a change in PPR in the VL and DM GPe
(Supplementary Fig. 14,15).

Upon quinpirole treatment, the accompanying changes in PPR exhibited a subregion-
specific reorganization under DA-depleted conditions. To provide complementary perspectives,
we analyzed both absolute PPR values and normalized changes relative to baseline. In the absolute
PPR values, DA depletion reduced baseline PPR selectively in the VL GPe, consistent with
previous reports showing decreased PPR following DA depletion43, and produced a robust
quinpirole-induced increase in the DM GPe (Supplementary Fig. 14b,c,e). These absolute
measures reflect basal differences in short-term plasticity (STP) and the absolute expression of
drug-induced changes. In contrast, normalized analyses, which highlight relative modulation
capacity rather than absolute baseline differences, revealed that DA depletion abolished the
quinpirole-induced facilitation of PPR in the DL GPe (Fig. 6b,f,g). In the VM GPe, facilitation
was still detectable but significantly attenuated compared to the contralateral side (Fig. 6e,f,g).
Conversely, in the VL and DM GPe, where PPR was largely unchanged by quinpirole under normal
conditions, DA depletion led to the emergence of a robust facilitation (Fig. 6c,d,f,g). Together,
these findings suggest that dopaminergic modulation of striatopallidal STP is differentially
affected by DA depletion in the DL-VM and VL-DM subregions of the GPe.

DA depletion induces region-specific alterations in the spatial distribution of presynaptic
D2Rs at striatopallidal axon terminals
In light of the possibility that variations in the spatial distribution and localization of D2Rs at
striatopallidal axon terminals may contribute to region-specific dopaminergic modulation of
striatopallidal transmission within the GPe, we further investigated whether DA depletion induces
region-specific alterations in the spatial distribution and localization of D2Rs. Striatopallidal axons
and axon terminals were labeled with GFP and RFP (mRuby), respectively, by injecting AAVs into
the entire striatum (Fig. 7a). Following 6-OHDA injection, we performed multi-color
immunostaining and utilized enhanced confocal imaging with airyscan in each subregion of the
GPe (Fig. 7b and Supplementary Fig. 12d,e). We replicated our findings from Figure 4,
demonstrating that D2Rs were more localized in the striatopallidal axons and axon terminals
within the DL and VM GPe compared to the VL and DM GPe in the contralateral hemisphere (Fig.
7c). To further delve into the spatial relationship between presynaptic D2Rs and striatopallidal
axon terminals in each subregion of the GPe, we conducted clustering analysis using Ripley’s H
function, which is particularly sensitive to spatial point patterns44,45. When the nearest distances
from striatopallidal axon terminals (RFP+) to D2Rs in the VL and DM subregions of the GPe were
used as a null model, clustering analysis revealed that the DL and VM GPe exhibited a greater
tendency for clustered features between striatopallidal axon terminals and D2Rs (Fig. 7e). The
results were reversed when the null model was replaced by the nearest distances from
striatopallidal axon terminals to D2Rs in the DL and VM GPe, indicating that striatopallidal axon
terminals and D2Rs appeared to be less clustered in the VL and DM GPe (Fig. 7e).

However, following DA depletion induced by 6-OHDA infusion, the differences in D2R
localization at striatopallidal axons and axon terminals between the DL-VM and VL-DM
subregions of the ipsilateral GPe were no longer observed (Fig. 7d). Under this DA-depleted
condition, the difference in the level of clustering between striatopallidal axon terminals and D2Rs
also became less pronounced between the DL-VM and VL-DM subregions of the GPe (Fig. 7f).
Interestingly, following DA depletion, the expression of D2Rs on striatopallidal axon terminals
increased significantly in the VL and DM GPe subregions (Fig. 7g). Moreover, the post-DA
depletion led to a marked enhancement in the clustering of striatopallidal axon terminals and D2Rs
in the ipsilateral GPe, in contrast to the contralateral GPe. This finding was further supported by
rejection rates exceeding 70%, calculated as the proportion of samples for which the null model
was rejected using the Diggle-Cressie-Loosmore-Ford (DCLF) test46 (Fig. 7h).

Under the same experimental conditions (Supplementary Fig. 16a), we also examined the
spatial relationship between dopaminergic boutons and striatopallidal axon terminals after DA
depletion. The co-localization of TH and vesicular monoamine transporter 2 (VMAT2)
immunofluorescence was considered indicative of potential dopaminergic boutons, while RFP
(mRuby)-positive fluorescence was used to identify putative striatopallidal axon terminals
(Supplementary Fig. 16b,c). We found no changes in the area of striatopallidal axons (GFP+) or
axon terminals (RFP+) within the GPe following DA depletion (Supplementary Fig. 16d,e).
Notably, in the contralateral hemisphere, more contact areas between dopaminergic boutons and
striatopallidal axon terminals (or axons) were observed in the DL and VM GPe compared to the
VL and DM GPe. This regional difference, however, was absent in the 6-OHDA-lesioned
ipsilateral hemisphere (Supplementary Fig. 16f). In the ipsilateral hemisphere, the areas of both
dopaminergic axons and boutons were significantly reduced across all GPe subregions
(Supplementary Fig. 16g). Furthermore, no significant differences in the nearest neighbor
distances between dopaminergic boutons and striatopallidal axon terminals were observed among
the GPe subregions, nor were there significant changes in the spatial relationship between
striatopallidal axon terminals (Supplementary Fig. 16h,i). Taken together, our findings reveal that
denervation of dopaminergic axons and DA depletion can lead to region-specific alterations in the
expression, localization, and spatial distribution of D2Rs on striatopallidal axon terminals within
the GPe. These changes may contribute to the functional modifications observed in the
dopaminergic modulation of striatopallidal transmission.

DA depletion may lead to region-specific changes in calcium dynamics at striatopallidal
synapses
To further investigate the physiological mechanisms underlying the heterogeneous dopaminergic
modulation of striatopallidal STP under both control and DA-depleted conditions, we utilized a
computational modeling approach based on the Tsodyks-Markram model, which describes the
dynamics of STP under general conditions47,48 (Fig. 8a). To define the parameter search space for
model optimization, we set lower and upper bounds for each parameter (Table S3). Consistent with
our quantal analysis (Fig. 3a-f), the computational model successfully reproduced the
experimentally observed subregion-specific patterns of dopaminergic modulation by incorporating
the calcium channel open probability as a key variable modulated by quinpirole49,50 (Fig. 8b).
Importantly, this computational model was deliberately constrained to presynaptic calcium
dynamics rather than incorporating the full GPe circuitry, thereby enabling direct validation with
axon terminal calcium imaging and PPR measurements. Under control conditions, the
computational model predicted a selective decrease in calcium channel open probability and
intracellular calcium concentration within the striatopallidal axon terminals of the DL and VM
GPe subregions (Fig. 8c-f). In contrast, under DA-depleted conditions, the model indicated a
marked reduction in calcium channel open probability and calcium concentration across all GPe
subregions, except for the DL GPe (Fig. 8g-j).

To directly assess presynaptic Ca2+ dynamics, we performed axon terminal calcium
imaging across GPe subregions (Supplementary Fig. 17). To selectively label striatopallidal axon
fibers, we injected an AAV expressing GCaMP6f into the whole striatum of Adora2A-Cre mice.
Fluorescence signals were recorded from bouton-like structures, and Ca2+ transients were
compared before and after quinpirole application in both control and DA-depleted conditions.
Under control conditions, quinpirole significantly reduced Ca2+ transients in the DL and VM GPe
subregions, whereas responses in the VL and DM GPe subregions were largely unchanged,
showing clear regional differences between GPe subgroups (Supplementary Fig. 17c,d). In contrast,
following DA depletion, quinpirole-induced suppression of Ca2+ signals was diminished in the DL
GPe, partially retained in the VM GPe, and newly observed in the VL and DM GPe, eliminating
the subgroup differences present under control conditions (Supplementary Fig. 17c,e).

To further validate the modeling framework, we compared the simulated outputs with the
experimental values of PPR and Ca2+ responses (Supplementary Fig. 18). The simulated and
experimental PPR values and Ca²⁺ responses were closely matched across subregions and
conditions, capturing the overall direction and variability of dopaminergic modulation
(Supplementary Fig. 18a,b). Representative overlays of experimental and simulated IPSCs further
revealed general correspondence in paired-pulse dynamics and temporal features (Supplementary
Fig. 18c). To provide a quantitative assessment of model performance, we computed the mean
squared error (MSE) and root mean squared error (RMSE) between simulated and experimental
values for each condition (Table S4). Overall, the model reproduced experimental PPR changes
and Ca²⁺ responses across subregions, although RMSE values were notably higher under 6-OHDA
conditions, indicating greater complexity of IPSC dynamics in the DA-depleted state51,52. Together,
these results suggest that DA depletion drives distinct synaptic adaptations at striatopallidal
synapses depending on their spatial locations within the GPe, further highlighting the region-
specific mechanisms that govern synaptic transmission in this nucleus.

Methods
Animals
All experimental procedures were conducted by protocols approved by the Institutional Animal
Care and Utilization Committee of the Ulsan National Institute of Science and Technology
(UNIST). All mice were maintained in C57BL/6J background. Mice were group-housed under a
12 hr light / dark schedule (lights on from 6 AM to 6 PM) and given ad libitum access to food and
water. Mice were group-housed (up to 5 mice per cage) and bred under standard pathogen-free
housing conditions in the animal facility of UNIST. Experiments included both female and male
mice in approximately equal proportions. Immunohistochemistry, FSCV, one-photon DA imaging,
and axon terminal Ca²⁺ imaging experiments were performed in adult mice aged 8–15 weeks.
Given the health and stability of GPe neurons in acute brain slices, patch-clamp recording
experiments were conducted in younger mice aged 3–4 weeks. To verify that the observed region-
specific modulation patterns also occur under adult conditions, additional recordings using low-
concentration DA (20 nM) were performed in adult mice aged 8-15 weeks, which reproduced the
same subregional patterns. To specifically express ChR2 in indirect pathway medium spiny
neurons (iMSNs), Adora2A-Cre (B6.FVB(Cg)-Tg(Adora2a-cre)KG139Gsat/Mmucd, MMRRC
stock number: 036158-UCD) mice were crossed with Ai32 (B6.Cg-Gt(ROSA)26Sortm32(CAG-
COP4*H134R/EYFP)Hze/J, Jackson stock number: 024109) mice, producing Adora2A-Cre;Ai32. These
mice were used for optogenetic stimulation of striatopallidal synaptic terminals in whole-cell patch
clamp recording experiments. To visualize striatopallidal pathway (axons and axon terminals),
Adora2A-Cre;Ai9 mice were generated by crossing Ai9-tdTomato (B6.Cg-
Gt(ROSA)26Sortm9(CAG-tdTomato)Hze/J) mice with Adora2A-Cre mice. These mice were also used in
immunohistochemistry experiments. Adora2A-Cre mice were used for immunohistochemistry and
fluorescence imaging experiments.

One-photon fluorescence imaging in the GPe in acute brain slices
Adult C57BL/6J mice were anesthetized via intraperitoneal injection of zoletil (60 mg/kg, Virbac
Korea) and rompun (15 mg/kg, Bayer Korea) mixture solution (zoletil : rompun : saline = 4 : 1 :
20), and AAVs expressing GRAB (AAV9-hSyn-rDA1.2a, 3.28 × 1013 vg/ml, WZ Biosciences) were
injected (250 nl per injection site at a rate of 100 nl/min) into the DLS (coordinates used, AP:
+1.3 mm from the bregma, ML: ±2.25 mm from the bregma, DV: −2.2 mm from the dura), the
GPe (coordinates used, AP: -0.45 mm from the bregma, ML: ±2.6 mm from the bregma, DV: −3.5
mm, -3.9 mm from the dura), and the M1 cortex (coordinates used, AP: +1.54 mm from the bregma,
ML: ±1.6 mm from the bregma, DV: −0.8 mm from the dura). Three weeks after virus injection,
the mice were deeply anesthetized with isoflurane (Piramal Critical Care), then decapitated and
the brains were immediately removed and briefly exposed to ice-chilled artificial cerebrospinal
fluid (ACSF) containing 125 mM NaCl, 2.5 mM KCl, 1.25 mM NaH2PO4, 25 mM NaHCO3, 1
mM MgCl2, 2mM CaCl2 and 15 mM glucose oxygenated with 95% O2 and 5% CO2. Acute brain
slices were prepared as 300-μm-thick sagittal sections using a tissue vibratome (Leica, VT 1200S).
One-photon imaging was performed using a BX51WI microscope (Olympus) equipped with a
40x/0.8 NA water-immersion objective (Olympus) and a SOLIS-565C high-power LED
(Thorlabs). A 565 nm LED was used to excite the rDA1.2a sensor, and fluorescence was collected
using a 569–594 nm filter (Chroma). Fluorescence images were further acquired using a scientific
complementary metal-oxide-semiconductor (sCMOS) camera (Orca-Flash4.0 V3, Hamamatsu) in
conjunction with HCImage Live software (Hamamatsu). For electrical stimulation, a bipolar
concentric electrode (CBAPB75, FHC) was positioned on the M1 cortex, GPe, and DLS under
fluorescence guidance. Dopamine release was evoked by electrical stimulation (0.2 ms pulse
duration, ten pulses), controlled using a DS-3 stimulus isolator (Digitimer, UK). Dopamine release
were imaged at a resolution of 512 x 512 pixels/frame, 10 frames/s, with an exposure time of 10
ms. For image analyses, regions of interest (ROIs) expressing rDA1.2a sensor were manually
selected and analyzed using ImageJ software (NIH).

Fast-scan cyclic voltammetry (FSCV)
To quantify and compare the magnitude of DA release across different basal ganglia nuclei, we
measured evoked phasic DA transmission using the WINCS Harmoni FSCV system85,86.
Following high-frequency electrical stimulation (100 Hz), we observed reliable DA release in the
GPe and DLS. Extracellular real-time DA release was measured using FSCV with carbon-fiber
microelectrodes (7 μm diameter carbon fiber enclosed in glass, with an exposed tip length of 50–
100 μm beyond the tapered glass seal) positioned in the GPe and DLS. A triangular waveform was
applied to the carbon fiber microelectrode (CFM) with a holding potential of -0.4 V, a switching
potential of 1.5 V, a scan rate of 400 V/s, and an acquisition frequency of 10 Hz, obtaining the
voltammogram (current-voltage curve). The initial signal detected in FSCV is the background
current, which is induced by ions near the CFM, but when DA is actually present, additional
oxidative current at +0.6 V and reductive current at -0.2 V are observed. Therefore, by utilizing
background subtraction to remove the signal in the absence of DA from the background
voltammogram, only the redox current response to DA remains, allowing real-time estimation of
DA concentration. To measure DA release induced by stimulation, a bipolar pulse was delivered
to each region with the following stimulation parameters: type, bipolar pulse; frequency, 100 Hz;
intensity, 300 μA; pulse width, 2 ms; duration, 4 sec (total of 400 pulses). All FSCV measurements
and stimulations were simultaneously performed using the WINCS Harmoni device and
WINCSware software. Calibration curves were obtained for DA concentrations of 20, 40, 60, 80,
100, 400, 700 and 1000 nM to convert DA oxidation current signals acquired by FSCV into actual
concentration values. To generate the calibration curves, linear regression analyses were performed
separately within the concentration ranges of 20 to 100 nM and 100 to 1000 nM.

Immunohistochemistry and confocal imaging
Mice were deeply anesthetized by intraperitoneal injection of zoletil (60 mg/kg, Virbac Korea) and
rompun (15 mg/kg, Bayer Korea) mixture solution (zoletil : rompun : saline = 4 : 1 : 20) and
perfused transcardially with phosphate buffer (PB), followed by 4% paraformaldehyde (PFA,
Sigma-Aldrich). Brains were rapidly removed and postfixed in 4% PFA at 4°C for overnight. Fixed
brains were transferred to 30% sucrose in 0.01 M PB for cryoprotection. Brain sections were made
into 20 μm thick sagittal slices using frozen section technique (Microtome SM2010, Leica).
Obtained free-floating brain sections were washed with PBS, PBST (0.5% Triton X-100) and
blocked with PBST containing 10% normal goat serum (NGS, Sigma-Aldrich) and 2% bovine
serum albumin (BSA, Sigma-Aldrich). After blocking, brain sections were incubated with an anti-
tyrosine hydroxylase antibody (rabbit polyclonal, 1:1000, ab112, Abcam), an anti-tyrosine
hydroxylase antibody (chicken polyclonal, 1:500, ab76442, Abcam), an anti-RFP antibody
(Guinea pig polyclonal, 1:1000, 390 005, Synaptic Systems), an anti-RFP antibody (mouse
monoclonal, 1:1000, MA5-15257, Thermo Fisher Scientific), an anti-GFP antibody (chicken
polyclonal, 1:1000, GFP-1010, Aves Labs), an anti-GFP antibody (mouse monoclonal, 1:1000, sc-
9996, Santa Cruz Biotechnology), an anti-bassoon antibody (guinea pig polyclonal, 1:500, 147
004, Synaptic Systems), an anti-bassoon antibody (mouse monoclonal, 1:500, ADI-VAM-PS003-
D, Enzo Life Sciences), an anti-VMAT2 antibody (rabbit polyclonal, 1:1000, VMAT2-Rb-Af720,
Nittobo Medical), an anti-GABA A Rα1 antibody (rabbit polyclonal, 1:2000, GABAARa1-Rb-
Af660, Nittobo Medical), an anti-synaptotagmin 1 antibody (mouse monoclonal, 1:1000, 105 011,
Synaptic Systems), an anti-synaptotagmin 7 antibody (rabbit polyclonal, 1:200, 105 173, Synaptic
Systems), an anti-synaptotagmin 5/9 antibody (rabbit polyclonal, 1:500, 105 053, Synaptic
Systems), an anti-VGAT antibody (rabbit polyclonal, 1:1000, 131 003, Synaptic Systems), an anti-
VGAT antibody (guinea pig polyclonal, 1:1000, 131 004, Synaptic Systems), an anti-Dopamine
D2 receptor antibody (rabbit polyclonal, 1:500, AB5084P, Sigma-Aldrich), an anti-Dopamine D4
receptor antibody (rabbit polyclonal, 1:500, PA5-28756, Thermo Fisher Scientific) in blocking
solution at 4℃ overnight, followed by secondary antibodies (goat anti-rabbit, goat anti-mouse,
goat anti-chicken, goat anti-guinea pig, 1:1000, Invitrogen) conjugated to Alexa 405, Alexa 488,
Alexa 594, and Alexa 647 fluorophores in blocking solution at room temperature for 2 hours. After
washing with PBST and PBS, brain slices were mounted onto slides using a mounting medium
(P36934 or P36935, Invitrogen).

For quantitative analysis, fluorescence images were captured by an FV1000 confocal laser
scanning microscope (Olympus) using a 40x/0.95 NA water immersion objective (zoom factor:
1.5, image size: 512 x 512 pixels), an LSM780N multi-photon confocal laser scanning microscope
with airyscan (Carl Zeiss) using a 63x/1.46 NA oil immersion objective (zoom factor: 3, image
size: 1248 x 1248 pixels), and an LSM880 multi-photon confocal laser scanning microscope with
airyscan (Carl Zeiss) using a 63x/1.4 NA oil immersion objective (zoom factor: 3, image size:
5827 x 5827 pixels for stitched images or 1248 x 1248 pixels). Imaging areas were randomly
selected and then images were captured from each target region. Images were further analyzed by
Zen software (Carl Zeiss), ImageJ program (NIH, measure function), and MATLAB (MathWorks,
custom codes). Confocal 3D images were acquired using the z-stack function of LSM880 confocal
laser scanning microscope with Airyscan. Images were collected at 0.185 μm intervals and 3.6993
μm depth with a 63x oil-immersion objective, 3x optical zoom, and a resolution of 1248 x 1248
pixels. 3D images were reconstructed and further analyzed by IMARIS 9.6 software.

Brain slice preparation for electrophysiology
Sagittal brain slices containing the GPe and striatum (250 μm thick) were prepared for whole-cell
patch clamp recording. Mice were anesthetized with isoflurane (Piramal Critical Care), decapitated,
and the brain was briefly exposed to cold ACSF containing 125 mM NaCl, 2.5 mM KCl, 1.25 mM
NaH2PO4, 25 mM NaHCO3, 1 mM MgCl2, 2mM CaCl2 and 15 mM glucose oxygenated with 95%
O2 and 5% CO2. Acute brain slices were obtained using a tissue vibratome (Leica, VT 1200S) in
ice-cold ACSF. Brain slices were first maintained in ACSF for 20 min at 34°C and then another 30
min at room temperature. For adult mice used in low-dose DA (20 nM) experiments, slices were
prepared in N-methyl-D-glucamine (NMDG)–based cutting solution (in mM: 93 NMDG, 2.5 KCl,
1.2 NaH2PO4, 30 NaHCO3, 20 HEPES, 25 glucose, 5 Na-ascorbate, 2 Thiourea, 3 Sodium Pyruvate,
12 N-Acetylcysteine, 10 MgSO4·7H2O, and 0.5 CaCl2·2H2O, 300 - 310 mOsm, pH 7.3 with HCl)
after transcardially perfused with an ice cold NMDG solution. Brain slices were immediately
transferred to 32°C NMDG solution for 10 min, followed by recovery in ACSF at room
temperature for 30 min. After recovery, slices were transferred to a submerged recording chamber
perfused with ACSF at a rate of 2 – 3 ml/min at 30 – 31°C. Brain slices were used for
electrophysiological recordings within 5 hours following slice preparation.

Electrophysiology, optogenetic stimulation, and pharmacology
GPe neurons were visually identified by conventional IR-DIC optics (BX51WI, Olympus). Whole-
cell voltage clamp recordings were made with borosilicate glass pipettes (3.5 – 5.5 MΩ) filled with
Cs+ based low Cl- internal solution containing 135 mM CsMeSO3, 10 mM HEPES, 1 mM EGTA,
3.3 mM QX-314, 0.1 mM CaCl2, 4 mM Mg-ATP, 0.3 mM Na3-GTP, 8 mM Na2-phosphocreatine
(290 – 300 mOsm, pH 7.3 with CsOH). To measure inhibitory synaptic currents from the GPe
neurons, the membrane potential was held at +0 mV (reversal potential of ionotropic glutamate
receptors) under the voltage clamp mode with liquid junction potential correction. Access
resistance was maintained between 10 – 20 MΩ, and only cells with less than a 20% change in
access resistance were included in the analysis. Whole-cell patch clamp recordings were performed
using Multiclamp 700B (Molecular Devices) and signals were filtered at 2 kHz and digitized at 10
kHz (NI PCIe-6259, National Instruments). Recording data were monitored and acquired by
WinWCP (Strathclyde software, http://spider.science.strath.ac.uk/sipbs/software_ses.htm), further
analyzed offline using Clampfit 10.7 software (Molecular Devices) and OriginPro 2017
(OriginLab). To stimulate ChR2-expressing striatopallidal axons, blue laser light (450 nm, 0.2 ms
pulses with 40 sec intervals, 50% of saturation power under the objective less than 1 mW) from
diode laser (MDL-III-450, Opto Engine LLC) was focused on the back focal plane of the objective
to generate wide-field illumination.

To examine the effects of quinpirole, recordings were divided into three epochs: baseline,
drug application (ON), and washout (OFF). For standard quinpirole experiments (10 µM), a stable
15-minute baseline was first obtained prior to drug application. Quinpirole was then bath-applied
for 10 minutes (quinpirole ON), followed by a 15-minute washout in drug-free ACSF (quinpirole
OFF). For low-dose quinpirole experiments (20 nM), a 10-minute baseline was obtained, followed
by a 10-minute drug application and a subsequent 15-minute washout. For each condition, data
points within the respective time window (baseline, quinpirole ON, quinpirole OFF) were
averaged to obtain a single representative value per cell for group-level statistical analysis. These
time windows were applied consistently within each experimental group, and the same definitions
were used for statistical analyses and figure presentations.

To test the physiological effects of D2-like receptors on striatopallidal GABAergic
transmission, we used the following agonists and antagonists: quinpirole, a DA D2-like receptors
agonist ((-)-Quinpirole hydrochloride, 20 nM, 100 nM, 10 M, Tocris, 1061), DA (Dopamine
hydrochloride, 20 nM, Tocris, 3548), A-412997, a D4R-selective agonist (A-412997
dihydrochloride, 100 nM, Tocris, 4552), and L-741626, a D2R-selective antagonist (L-741,626,
100 nM, Tocris, 1003). For antagonist experiments using L-741626, a lower concentration of
quinpirole (100 nM) was used to avoid masking the antagonist effect. These drugs were bath-
applied during the recording session after stable baseline IPSC traces were established. To measure
the paired pulse ratio (PPR) and ongoing activity of GABA transmission at striatopallidal synapses
in the GPe subregions, we optogenetically stimulated striatopallidal axon terminals by using paired
light stimuli (50 ms interval) for PPR assessment and trains of 10 light pulses at 20 Hz for ongoing
activity, respectively. This interstimulus interval (ISI) was selected based on established protocols
for PPR measurement using ChR229–31. For the experiment measuring strontium-induced
asynchronous GABA release from striatopallidal synaptic terminals, strontium chloride
hexahydrate (4 mM, Sigma-Aldrich, Cat. No. 255521) was added to the ACSF in place of calcium.
After recording oIPSCs in normal ACSF, the calcium-containing ACSF was replaced with
strontium-containing ACSF. The amplitude and frequency of strontium-induced asynchronous
IPSCs were analyzed using Mini Analysis software (Synaptosoft). To quantify the relative
suppression level of ongoing activity from individual IPSCs, the charge ratio was calculated using
the following equation (1)29.

R = (QT / Qbaseline) / (Amp1 / Amp1baseline) (1)

Clustering analysis of strontium miniature responses
To assess whether miniature IPSC features differ systematically across GPe subregions, we
performed an unsupervised clustering analysis of strontium-induced miniature responses. This
approach allowed us to capture subtle multivariate structure in amplitude, rise time, and decay
constant distributions, and to test for region-specific deviations beyond simple univariate
comparisons. Strontium mini responses were analyzed using Mini Analysis software (Synaptosoft).
1. Quantification and statistical analysis
Miniature IPSC features {amplitude (AMP), rise time (RT), decay constant (DT)}
were merged into a single matrix with corresponding region labels in MATLAB.
Miniature responses containing any missing value (NaN) were discarded.
Subsequently, outliers whose AMP, RT, or DT fell outside the [0.01, 99.99]
percentile of the corresponding marginal distribution were also discarded. Finally,
each feature was z-standardized along each marginal distribution (μ = 0, σ = 1).
2. Recursive k-means subclustering
To capture substructure without over-fragmentation, we implemented a recursive k-
means clustering method (recursiveKMeansAuto). At every cluster, the optimal k (2
≤ k ≤ 10) was determined with the Calinski–Harabasz (CH) index. A cluster was
split only when (i) its size exceeded 500 miniature responses and (ii) the optimal k
increased the CH gain ≥ 5 % relative to k = 2. Empirically, the 500 counts threshold
guarantees an expected count ≥ 20 for each of the four regions in the subsequent χ²
test, while the 5% CH increment threshold filters out marginal improvements that are
rarely reproducible in biological replicates.
3. Cluster × region contingency testing
For every cluster, a 4 × 2 contingency table was assembled (rows = regions;
columns = inside vs. outside c). Clusters containing fewer than n = ⌈ 20 / min(p_r) ⌉
(2), where p_r is the global proportion of region r, were excluded so that each region
retained an expected count ≥ 20. Tables were evaluated with Pearson’s χ² (d.f. = 3);
standardized residuals Z = (O_cr - E_cr) / sqrt(E_cr) (3) were used to quantify
region-specific deviations (excesses or deficits).
4. Region-wise deviation and pairwise contrasts
A region’s overall contribution to the global χ² statistic was defined as S = ∑ Z^2 (4).
Significance was assessed by randomly permuting region labels 10,000 times. To
compare regions directly, we computed ΣZ² differences (ΔS) and obtained
permutation p-values with the same 10,000 null replicates. Raw p-values were
adjusted both by Holm–Bonferroni (controlling the family-wise error rate at 0.05)
and by the Benjamini–Hochberg procedure (false-discovery rate 0.05).
5. Visualization
Heat maps depict ΔS values with significant comparisons marked by asterisks (Holm-
corrected p < 0.05). A normalized bar plot illustrates the magnitude of VL’s deviation
relative to the other three regions; horizontal bars rank regions by ΣZ², annotated with
permutation p values, and a permutation cloud plot overlays observed ΣZ² (red stars) on
10,000 null draws (gray).

Biocytin labeling and immunostaining of biocytin-filled neurons
For examining the cell type of the recorded GPe neurons, Cs-based internal solution containing
0.2% biocytin (B4261, Sigma-Aldrich) was loaded into GPe neurons for 20 min. After the delicate
retraction of the glass pipette, brain slices were fixed in 4% PFA overnight at 4°C. On the following
day, slices were washed with PBS, PBST for 1 hours and blocked with solution containing 10%
NGS and 2% BSA for 4 hours. After blocking, brain sections were incubated with an anti-
Parvalbumin antibody (guinea pig polyclonal, 1:1000, 195 004, Synaptic Systems) and an anti-
FOXP2 antibody (rabbit polyclonal, 1:500, ab16046, Abcam), in blocking solution at 4℃ for 3
days, followed by secondary antibodies (goat anti-rabbit, goat anti-guinea pig, 1:1000, Invitrogen)
conjugated to Alexa 594 and Alexa 647 fluorophores and Alexa 405-conjugated streptavidin (1:500,
Invitrogen) in blocking solution at 4℃ for 2 days. After washing with PBST and PBS for 12 hours,
brain slices were mounted onto slides using a mounting medium (P36934, Invitrogen). Images
were obtained by an FV1000 confocal laser scanning microscope (Olympus) and an LSM880
multi-photon confocal laser scanning microscope with airyscan (Carl Zeiss). Recorded neurons
were classified as PV-positive or FOXP2-positive based on the colocalization of biocytin labeling
with immunostaining signals, which were examined and confirmed using ImageJ59,62.

Virus purchase
AAV9-hSyn-rDA2h was purchased from WZ Biosciences, with permission from Dr. Yulong Li
(Peking University School of Life Sciences). The production titer was 3.28 × 1013 virus
molecules/ml. AAV9-Syn-Flex-GCaMP6f-WPRE-SV40 was purchased from Addgene (100833-
AAV9). The production titer was 2.20 × 1013 genome copy/ml.

AAV vector production
For adeno-associated virus (AAV)-based synaptophysin expression, we purchased pAAV-hSyn-
FLEx-mGFP-2A-Synaptophysin-mRuby (Addgene, #71760), which allows expression of mGFP
and Synaptophysin-mRuby in Cre-expressing neurons. AAVs were thereafter purified by iodixanol
gradient ultracentrifugation by the KIST Virus Facility. The production titer of virus was as follows:
pAAV-hSyn-FLEx-mGFP-2A-Synaptophysin-mRuby (1.19 × 1013 genome copy/ml).

Stereotaxic viral injection for striatopallidal axon labeling
Stereotaxic virus injections for striatopallidal axon labeling were conducted in Adora2A-Cre mice.
Mice were deeply anesthetized by intraperitoneal injection of zoletil (60 mg/kg, Virbac Korea) and
rompun (15 mg/kg, Bayer Korea) mixture solution (zoletil : rompun : saline = 4 : 1 : 20) and
mounted in a stereotaxic frame (51730, Stoelting). A small hole was drilled after exposing the skull,
and AAVs were injected through a glass micropipette with a long, narrow tip (size: 10 – 20 μm),
which was fabricated using a micropipette puller (P-1000, Sutter Instrument). The glass pipette
was slowly advanced to the coordinates specified for each target area and left in place for 5 min
prior to virus injection. The virus solution was injected at an infusion rate of 100 nl/min, and the
glass pipette was withdrawn 10 min after the completion of the injection. Following the injection,
the scalp was sutured, and the mice were returned to their home cages for a minimum of 21 days
before the subsequent experiments. A total volume of 1600 nl virus solution (400 nl per injection
site, AAV5-hSyn-Flex-mGFP-2A-Synaptophysin-mRuby) was injected into the striatum
(coordinates used, AP: +0.8 mm, ML: ±2.65 mm from the bregma, DV: -4.2 mm and -2.5 mm for
the lateral striatum from the exposed dura mater, AP: +0.85 mm, ML: ±2.00 mm from the bregma,
DV: -3.2 mm and -1.85 mm for the medial striatum from the exposed dura mater) to achieve
sufficient viral expression across the entire population of striatal neurons. Mice injected with the
virus were subsequently used for immunohistochemistry 6 weeks post-injection.

Stereotaxic 6-OHDA injection
Stereotaxic 6-OHDA injections were conducted on mice (Adora2A-Cre, Adora2A-Cre;Ai32, and
Adora2A-Cre;Ai9) using a stereotaxic system (51730, Stoelting). Before surgery, mice were
deeply anesthetized by intraperitoneal injection of zoletil (60 mg/kg, Virbac Korea) and rompun
(15 mg/kg, Bayer Korea) mixture solution (zoletil : rompun : saline = 4 : 1 : 20). A total volume
of 300 nl 6-OHDA solution (2.5 mg/ml, dissolved in 0.9% sterile saline with 0.02% ascorbic acid)
was injected unilaterally into the left MFB (coordinates used, AP: -0.7 mm, ML: +1.2 mm from
the bregma, DV: -4.80 mm from the exposed dura mater for mice aged 3 to 4 weeks, AP: -1.2 mm,
ML: +1.2 mm from the bregma, DV: -4.75 mm from the exposed dura mater for mice older than 8
weeks). A glass micropipette with a long, narrow tip (size: 10 – 20 μm) was made using a
micropipette puller (P-1000, Sutter Instrument) to deliver 6-OHDA. The glass pipette was slowly
advanced to the target area and left in place for 5 min prior to the 6-OHDA injection. 6-OHDA
solution was injected at an infusion rate of 100 nl/min, and the glass pipette was withdrawn 10 min
after the end of injection. After the injection, the scalp was sutured, and the mice were returned to
their home cages. Mice injected with 6-OHDA were used for electrophysiology and
immunohistochemistry experiments at 1, 3, 5, and 7 days post-injection21,87.

Spot detection and synapse extraction analysis
Spot detection and synapse extraction analysis were performed similarly as previously
described21,88,89. To extract synapses from the acquired images, we implemented a general method
for spot detection. The method utilizes mathematical morphological processing based on set theory.
Signal enhancement and spot detection can be achieved by treating objects within images as sets
and utilizing combinations of logical operators in set theory. This method consists of three steps:
denoising, signal enhancement, and spot extraction. In the denoising step, the acquired images are
processed using Gaussian filter with σ = 0.5. For signal enhancement, a combination of three
thresholding algorithms with top-hat transform, hard thresholding, and Otsu thresholding are
applied to the resulting images. Top-hat transform of an image I(m) is represented as equation
(5):

T(I(m)) = I(m) - I(m) ∘ s(m) (5)

where ° denotes the opening operator in morphological processing and s(m) denotes the
structuring element. Our structuring element s(m) for applying top-hat transform is circular
shape with size of 10 X 10. Hard thresholding is expressed as equation (6):

H(I(m)) = I(m) if I(m) > threshold; 0 if I(m) < threshold (6)

Threshold value of hard thresholding is 45000. After applying top-hat transform and hard
thresholding to the acquired images, Otsu’s thresholding method is exploited to the processed
images to enhance fluorescent signal from the actual objects while suppressing background noise.
From the signal-enhanced images, spots are extracted using a combination of morphological filters,
which include two key operations: filling and opening. The filling is used to fill out holes in
fluorescent spots, while the opening operation smooths spot contours and removes irrelevant
fluorescent signals unrelated to synaptic structures. The extracted spots are clustered within the set
of images (presynaptic and postsynaptic) corresponding to distance among the spots, which allows
the images to delineate presynaptic and postsynaptic structures. By calculating the distance
between presynaptic and postsynaptic clusters, those with a separation of less than 1 pixel (40 nm)
were merged to form synapses.

Point pattern analysis
The spatial analysis of clustered features between striatopallidal axon terminals and D2Rs was
conducted using Ripley’s analysis on both single group and group vs. group scale90. Ripley’s
function describes spatial characteristics of the sample (clustering or dispersion) over a range of
distances. The edge corrected Ripley’s function is defined as equation (7):

K(r) = λ^-1 ∑ i≠j k_ij I(d_ij ≤ r) / N (7)

where λ is the density of a point pattern; k_ij is the inverse of a portion of circumference with
center at point i and radius r, that lies within the boundary and passes through point j; function
I is an indicator function; d is the Euclidean distance between points i and j; N is the number of
points in the pattern. A variance stabilized version of the Ripley’s K function, defined in equation
(8), was used in this study:

H = sqrt(K(r) / π) - r (8)

Ripley's function was calculated for each observed point pattern. Group vs. group analysis was
also used to determine whether point patterns from one group had similar spatial properties with
patterns from another (null) group. We assume that all m (the total number of generated patterns)
patterns in the null group are generated using the identical point method.

Diggle-Cressie-Loosmore-Ford (DCLF) test
Diggle-Cressie-Loosmore-Ford (DCLF) test was performed similarly as previously described21,91.
The DCLF test quantifies the difference between the H function of the observed pattern and the H
function for the null group at the given spatial scale. We computed H(r) for the test pattern
H_obs(r) and each pattern in the null group H_i(r), then we estimated the summary function H´(r)
for the null group as in equation (9):

H´(r) = 1 / (m+1) * (H_1(r) + H_2(r) + ... + H_m(r) + H_obs(r)) (9)

Then, the maximum vertical separation between H(r) and H´(r) is defined as in equation (10):

T_obs = ∫_0^R (H_obs(r) - H´(r))^2 dr (10)

where R is maximum value of the interaction distance. To compute p-value, the following formula
can be used: p = ∑_i=1^m I(T_obs > T_i) / (m+1), where I(T_obs > T_i) = { 1, T_obs > T_i; 0, otherwise } (11) and T_i is computed
between the observed pattern and each pattern in the test group (i = 1,m).

Computational model of synaptic transmission
A computational model is based on the Tsodyks-Markram model47 to simulate synaptic responses
and to understand the underlying mechanisms affecting neurotransmitter release probability and
synaptic plasticity under different experimental conditions. The model incorporated both
facilitation and depression dynamics, adapting established frameworks for synaptic transmission
modeling. The following list outlines the key variables and parameters utilized in this modeling
approach.

The model included the following key variables:
u(t): Utilization of synaptic resources at time t.
R(t): Fraction of resources in the recovered state at time t.
n(t): Vesicle availability at time t.
Ca(t): Intracellular calcium concentration at time t.
P(t): Release probability at time t.
IPSC(t): Inhibitory postsynaptic current at time t.

Key parameters were defined as:
P0: Baseline release probability.
Kc: Dissociation constant for calcium's effect on release probability.
τf: Facilitation time constant.
τd: Depression time constant.
τrec: Recovery time constant.
τCa: Calcium decay time constant.
[Ca]influx: Amplitude of calcium influx during action potentials.
PopenVGCC: Probability of calcium channel opening.

Mathematical framework
The model was governed by a set of differential equations (equations (12-17)):
1. Calcium dynamics:
dCa/dt = (Ca_0 - Ca(t)) / τCa + δ_spike * P_openVGCC * [Ca]influx (12)
where [Ca_0] = 50 nM92,93 is the baseline calcium concentration, and δ_spike is 1 at spike
times and 0 otherwise.
2. Release probability:
P(t) = P0 * ([Ca(t)]^m / (Kc^m + [Ca(t)]^m)) (13)
where m = 4 is the Hill coefficient for calcium effect on release probability94,95.
3. Vesicle availability:
dn/dt = (n_∞ - n(t)) / τrec - δ_spike * u(t) * R(t) * n(t) (14)
4. Utilization of synaptic resources:
du/dt = -u(t) / τf + δ_spike * R(t) * (1 - u(t)) (15)
5. Recovery of synaptic resources:
dR/dt = (1 - R(t)) / τrec - δ_spike * u(t) * R(t) * n(t) (16)
6. Inhibitory postsynaptic current:
IPSC(t) = IPSC(t) + A(t) * e^(-(t-t_spike)/τIPSC) (17)
where A(t) = u(t) * R(t) * n(t) and τIPSC = 0.02 is the time constant for IPSC decay.

Simulation protocol
Simulations were conducted over a 1-second duration with a time step of dt = 0.001 seconds.
Action potentials were simulated at 0.5 and 0.55 seconds to represent paired-pulse stimulation.
The differential equations were numerically integrated using the Euler method. Initial conditions
were set based on physiological values, and variables were constrained to remain within plausible
biological ranges to prevent computational errors.

Parameter optimization
An optimization routine was employed to fit the model to the experimental PPR data. The objective
function minimized the squared difference between the simulated PPR and the observed mean PPR
for each condition. The optimization process involved:
1. Control condition: Parameters were initially optimized for the control condition using the
differential evolution. To ensure physiological plausibility, bounds were specified for
each parameter, and the number of iterations was capped at 100. To accurately capture
the synaptic behavior observed in different conditions, the bounds for the baseline release
probability (P0) were dynamically adjusted based on the observed paired-pulse ratio
(PPR). Specifically, for the facilitating synapses (PPR > 1.05) the bounds for P0 were set
to (0.1, 0.5). This range allows P0 to vary within values that support an increasing release
probability upon successive stimuli, characteristic of facilitating synapses. For synapses
that are non-facilitating or depressing (PPR ≈ 1 or PPR < 1) the bounds for P0 were
adjusted to (0.55, 0.9).
2. Quinpirole condition: Starting from the optimized control parameters, scaling factors
were introduced to simulate the effect of quinpirole, a dopamine D2 receptor agonist on
the VGCC open probability (P_openVGCC). To isolate the effect of dopamine on synaptic
dynamics, we constrained the model such that only the calcium channel open probability
was allowed to vary between baseline and quinpirole conditions, consistent with prior
evidence that D2-like receptor activation modulates presynaptic calcium influx96–99. The
optimization aimed to reproduce the observed changes in PPR under quinpirole treatment.
In this case the scaling parameter for the P_openVGCC was optimized, while the rest of the
parameters remained the same as in the optimized ‘control conditions’. If the synapses
changed from non-facilitating (PPR ≈ 1) to facilitating (PPR > 1) under ‘quinpirole
condition’, the following parameters were manually adjusted to guarantee facilitation.

To ensure robustness and reproducibility of the model fitting, we performed multiple independent
optimizations to the mean paired-pulse ratio (PPR) measured under baseline and quinpirole (QP)
conditions for each experimental group (control and 6-OHDA). For each condition, the model was
fit several times using different random initializations of the full parameter set. This approach was
designed to avoid reliance on a single local optimum and to assess whether consistent parameter
changes emerge across fits. All fits were performed independently, and only those that produced
physiologically plausible values and minimized the squared error between simulated and observed
PPR were retained for downstream analysis. This procedure ensured that the reported effects were
robust and not dependent on specific fitting trajectories or initial conditions. For the 6-OHDA
condition, model parameters were optimized independently using the same procedure described
above for the control condition. For the 6-OHDA + quinpirole condition, the model was fit as
described for quinpirole, by optimizing a scaling factor on VGCC open probability while keeping
all other parameters fixed.

Statistical analysis and exclusion criteria for computational modeling
Statistical comparisons between conditions were performed using non-parametric tests due to the
sample size and data distribution. The Wilcoxon Signed-Rank Test was applied for paired
comparisons of parameters, and the Mann-Whitney Test was applied for unpaired comparisons
within the same cells under different conditions. Cells were excluded from analysis if the simulated
PPR under quinpirole did not match the observed behavior (e.g., the model predicted facilitation
when depression was observed experimentally, or vice versa).

Model performance evaluation
To assess the quality of model fits, we compared simulated outputs with the corresponding
experimental PPR values and Ca2+ fluorescence signals across all GPe subregions and conditions
(control and DA depletion). Model error was quantified using the mean squared error (MSE) and
the root mean squared error (RMSE), defined as the square root of the average squared difference
between simulated and experimental PPR values. These metrics provide a direct measure of
deviation from experimental targets while retaining biological units. Representative overlays of
simulated and experimental IPSC traces, as well as comparisons of simulated versus experimental
PPR distributions, were also generated to visually confirm model performance. All numerical
values of MSE and RMSE are reported in Table S4.

Software and libraries
All computations were performed using Python 3.9, with key libraries including:
NumPy: For numerical computations and array manipulations.
SciPy: For optimization routines and statistical tests.
Pandas: For data handling and manipulation.

Calcium imaging of striatopallidal axonal boutons in acute brain slices
For imaging cytosolic Ca2+ concentration at axonal boutons, Cre-dependent GCaMP6f was
expressed across the striatum. AAV9-Syn-Flex-GCaMP6f-WPRE-SV40 was diluted 1:2 in
autoclaved PBS immediately before use. A total of 1600 nl virus was injected bilaterally (400 nl
per site) at the following coordinates relative to bregma to achieve broad expression across the
striatum (coordinates used, AP: +0.8 mm, ML: ±2.65 mm from the bregma, DV: -4.2 mm and -2.5
mm for the lateral striatum from the exposed dura mater, AP: +0.85 mm, ML: ±2.00 mm from the
bregma, DV: -3.2 mm and -1.85 mm for the medial striatum from the exposed dura mater). Acute
brain slices containing the striatum and GPe were prepared 3 weeks after the viral injection,
described in ‘Brain slice preparation for electrophysiology’ section. For imaging, slices were
transferred to a chamber perfused with carbogenated ACSF at 2–3 ml/min using a peristaltic pump
(Miniplus 3, Gilson). Ca2+ signals were acquired on a A1R MP⁺ confocal microscope (Nikon).
Ca2+ images were obtained using a krypton/argon laser (488 nm excitation and > 495 nm emission)
and acquired at 2 frames/s with 256 x 256 pixels for ~30 sec. For the evoked synaptic release at
the axon terminals, the tungsten bipolar electrode was placed in the striatum and oriented obliquely
to align with the presumed trajectory of striatopallidal axon fibers. Synaptic responses were evoked
by 20 Hz stimulation (200 μA, 0.1 ms duration for 1.0 sec) via a constant current isolation unit
(A365, World Precision Instruments). To assess the effect of D2-like receptor activation on axon-
terminal Ca2+ signals, 10 μM quinpirole was bath-applied for at least 4 minutes. All the solutions
were bubbled with 95% O2 and 5% CO2 (pH 7.4). Image sequences were analyzed in MATLAB
(MathWorks). We segmented putative boutons by Otsu-based thresholding with user-adjusted
contrast and additionally screened by manually to exclude non-punctate or artifactual ROIs.
Calcium transients were calculated as ΔF/F = (F − F0) / (F0 − Fb), where F0 is the baseline
fluorescence measured before quinpirole application (Base condition) and Fb is the background
fluorescence defined from a manually selected background ROI.

Statistics and reproducibility
All data were analyzed using the following software: Clampfit 10.7 (Molecular Devices), Mini
Analysis (version 6.0.7, Synaptosoft), OriginPro 2017 (OriginLab), Zen software (version 2.5,
Carl Zeiss), ImageJ (version 1.53c, NIH), and MATLAB (version R2021a, MathWorks).
Statistical analyses were performed using GraphPad Prism (version 10, GraphPad software).
Summary statistics were presented as either box-and-whisker plots (center line, median; box limits,
25th and 75th percentiles; whiskers, minimum to maximum values) or mean ± SEM. Two-tailed
unpaired and paired student’s t-tests, one-way ANOVA with two-sided Holm-Sidak’s post-hoc
multiple comparison test, two-way repeated measures ANOVA with two-sided Holm-Sidak’s
post-hoc multiple comparison test, two-tailed one-sample t-test, linear regression, and the
Kolmogorov-Smirnov test were employed to assess statistical differences (two-sided) between the
groups. A P-value of less than 0.05 was considered statistically significant and exact P-values are
provided in the legends unless P < 0.0001. Significance levels are also denoted as follows: *p <
0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001. Statistical tests were primarily applied to
datasets involving discrete group comparisons. Panels such as Fig. 1b,h, Fig. 2e, Fig. 4e,k, and
Fig. 7e,f,h present time-course traces, cumulative probability distributions, or computational
simulations. These are provided to show representative biological trends and data distributions;
thus, they were excluded from formal group-wise statistical comparisons, with detailed
quantitative summaries provided in the associated summary plots. All experiments were
independently repeated at least three times with similar results. In the legends, n is defined as the
number of technical replicates (e.g., independent slices or cells) followed by the number of
independent biological replicates (mice) from which they were derived. For all
electrophysiological experiments, the individual cell was defined as the primary unit of statistical
analysis to account for the intrinsic physiological variability between neurons. To ensure
transparency regarding the hierarchical nature of the data, the number of biological replicates
(mice) is explicitly provided alongside the technical replicates in the legends. We did not observe
obvious batch effects or systematic differences between cells recorded from the same animal.
Sample sizes were not pre-determined by statistical methods but are comparable to those
commonly used in the field. Exact statistical values for all main figures are provided in Table S5.

Data availability
Source data are provided with this paper. All numerical data underlying the figures (including
simulation outputs) are compiled in the accompanying Source Data Excel file and are archived on
Zenodo (DOI: 10.5281/zenodo.18608880).

Code availability
Python and MATLAB code used for data analysis and simulations in this study are publicly
available on Zenodo (DOI: 10.5281/zenodo.18608880). The corresponding GitHub repository is
available at https://github.com/yelee03153/Striatopallidalsynapse.git

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The manuscript by Lee and colleagues utilizes viral tracing, IHC, imaging, slice electrophysiology and optogenetics, and D2-like receptor agonist application to examine the impact of D2/4R activation on striatopallidal transmission. The main result is that quinpirole lowers the initial probability of striatopallidal transmission at DL and VM GPe neurons through activation of pre-synaptic D2Rs and quinpirole or a D4R dopamine agonist reduces striatopallidal transmission through activation of postsynaptic D4Rs in GPe neurons throughout the nucleus. In addition, the authors provide viral tracing and IHC data supporting the idea that dopaminergic synapses are closer to striatopallidal synapses and striatopallidal D2Rs are more abundant in DL and VM GPe consistent with stronger presynaptic modulation. Overall, these findings argue for unexpected complexity in extrastriatal dopaminergic modulation mechanisms. In general, the experiments are technically well done but the use of exogenous D2/4R agonists at high concentrations leaves a key question unanswered: does native DAergic transmission also modulate striatopallidal transmission through activation of presynaptic and postsynaptic D2Rs and D4Rs respectively. Dual optogenetic stimulation of GPe DA axons and striatopallidal axons in combination with antagonist application should be used to answer this point.\nI have several other questions/points that the authors should address:\n1. The authors reveal a GPe GRABDA signal upon GPe electrical stimulation that is 10X less than that in the striatum. While expected given the lower density of DA axons in GPe, absolute quantification of the amounts released in both structures with GRAB DA and/or FSCV would be ideal. Also could the striatal GRABDA signal be saturated given its high affinity, in which case the differences in DA release between striatum and GPe could be even greater. Answering these questions would tell us whether the levels of synaptically released DA are sufficient to activate D2-like receptors in the GPe.\n2. Consistent with previous studies the authors find that DA fibers more abundant in specific GPe regions. Are the amounts of DA released in these regions consistent with the innervation pattern?\n3. The reported differences in quantal properties and synaptotagmin expression are interesting but do not explain the data.\n4. Why is the effect of quinpirole on PPR in DL and VM GPe sensitive to D4R antagonism?\n5. Why differences in the speed of degeneration of DAergic axons in GPe regions following 6-OHDA MFB injection are relevant is unclear.\n6. 3 days after 6-OHDA injection DL and VM GPe no longer show a PPR increase with quinpirole but DM and VL GPe do. These effects are also associated with a reduction in presynaptic D2Rs in DL and VM GPe and an increase in presynaptic D2Rs in DM and VL. The relevance of this finding to the rest of the paper should be more thoroughly discussed. Given the short time between the lesion and the measurement these data do not inform PD pathophysiology.\n7. The model used to investigate striatopallidal transmission mechanisms was not sufficiently informed by GPe biology to be useful.", "reviewer_2": "This manuscript describes a tour de force by the authors in teasing out key regional differences in dopaminergic innervation and modulation in the GPe. The results appear rigorous and robust, as the authors thoroughly assess regional differences using multiple methodological approaches. These findings contribute to the field by showing how dopamine differentially modulates striatopallidal synapses in the indirect pathway, depending on the region within the GPe. These results have implications for understanding how dopamine depletion in Parkinson’s disease affects the GPe.\nOverall, this is a compelling, well-written manuscript presenting many experimental results using a wide range of methods in a clear and organized way. I have only two major critiques, which, if addressed, would improve the clarity and impact of the manuscript. I focus primarily on the computational methods employed, as that is my area of expertise.\n1. Computational Model\nThe inclusion of a phenomenological short-term synaptic plasticity model adds value to the study and has the potential to generate experimentally testable predictions. However, the description of the modeling method needs clarification. Multiple models appear to be generated for each condition: Control (baseline vs. QP) and 6-OHDA (baseline vs. QP). Are these independently fit to different experimental recordings, followed by statistical comparisons between the populations? The methods explain how the control and QP conditions were fit, but not how the 6-OHDA models were generated. The fitting procedure should be described more clearly and quantitatively assessed.\nWhy do the authors choose calcium channel open probability as the only free parameter between control and QP conditions? If the model is constrained to vary only one parameter to fit known experimental differences (e.g., in PPR), then the conclusion that calcium channel open probability is the key mechanism is built into the model itself. In that case, it's unclear what new insight the model adds—particularly if no comparison is made between model fits across conditions. Expanded discussion of what the modeling contributes would strengthen this section. For example, if a change in calcium channel open probability results in a model that fits the QP data as well as the baseline model fits baseline data, that would better support the proposed mechanism. Including an assessment of model goodness-of-fit, example traces comparing model to experimental data, and error levels from the optimization would be helpful.\n2. AI-based Strontium Mini Clustering Analysis\nThe methods for the “AI-based” clustering analysis lack clarity and rationale. Why use PCA when the data are already low-dimensional (three parameters)? Why choose 50 clusters for k-means? A rationale for this choice would be helpful. The repeated t-tests comparing regions also appear not to correct for multiple comparisons—this should be either justified or corrected. Finally, the term “AI-based” is somewhat misleading, as these are standard statistical methods.", "reviewer_3": "Lee et al. used a combination of electrophysiological, pharmacological, imaging, and computational techniques to determine the influence of dopaminergic innervation on striatopallidal transmission. Results indicate that activation of presynaptic D2 receptors and postsynaptic D4 receptors weakens striatal inhibitory inputs to the GPe in a subregion-dependent manner. Furthermore, the authors demonstrate that dopamine depletion leads to subregion-specific presynaptic D2 receptor changes. The results further our understanding of subregional differences in the GPe and basal ganglia dysregulations after dopamine depletion.\nWhile this paper addresses an important question, it may not be of broad interest to the larger neuroscience community and may be better suited for a more specialized audience. In addition, there are significant concerns about the methodology and analysis that weaken the potential impact of this study.\nMajor concerns:\n1. The age of mice used for patch clamp experiments is different from the age of the mice in the histological experiments. This is confusing as the methods state ‘most experiments’ were in adult mice while all electrophysiology experiments are in 3-4 week old mice. The electrophysiological experiments are ‘most experiments’ in this paper and the inconsistency in age across experiments limits the conclusions that can be drawn. In addition, 3-4 week old mice are still undergoing many neurological changes including those in the basal ganglia, and may not represent the state of the GPe in adult animals.\n2. The statistical comparison between 100% baseline values to the percent change during drug application (e.g. quinpirole) for oIPSC and PPR recordings (e.g., Fig. 2; Fig. 3g,i; Extended Data Fig. 6,8,9) does not make sense. The authors should compare the quinpirole washon to time-matched vehicle washon controls to accurately capture natural variability across cells over time. Or at the very least, the authors should do paired comparisons of the raw (non-normalized) values between the baseline value and the drug values.\n3. The authors claim that the effect of quinpirole on PPR in the DL and VM is different from that in the VL and DM regions, but this is not directly compared. The authors draw this conclusion from whether the PPR is significantly different from baseline or not significantly different from baseline in each region (lines 186-192). A significant effect in one region and the fact that there is no significant effect in another region does not mean that the quinpirole effect in those two regions is significantly different from each other. To claim that quinpirole has a different effect on PPR between subregions, the magnitude of the quinpirole effect (e.g. the percent difference from baseline) in one region should be compared to the magnitude of the quinpirole effect in the other region. Either an ANOVA across all four regions for % of baseline, or at least a direct test of DL/VM vs VL/DM should be conducted.\n4. In the 6-OHDA experiments, again the authors take the presence or absence of statistical differences as a comparison between groups. The fact that something is significant in the contralateral hemisphere, but not significant in the ipsilateral hemisphere, is not a valid comparison. For example, TH area is compared between subregions within the contralateral hemisphere and then compared within the ipsilateral hemisphere (Extended Data Fig. 7e). In order to determine subregional differences in susceptibility to dopamine depletion the authors should compare the ipsilateral hemisphere values (normalized to contralateral as in extended figure 7d) for each region to each other region. In other words, the data in extended figure 7e (bottom), but use the normalized values rather than absolute TH area values. This would tell you whether the magnitude of the 6-OHDA effect differs by region.\n5. The authors note differences in normalized PPR during QP ON compared to 100% baseline between the ipsilateral (Fig. 6b-e) and contralateral (Extended Data Fig. 8) hemispheres and conclude that dopamine depletion reverses PPR responses to quinpirole in all four subregions (lines 374-380). However, the comparisons of normalized PPR (Fig. 6f) or non-normalized PPR (extended figure 9j) during QP ON between ipsilateral and contralateral hemispheres show no difference in any subregion aside from DM. Thus, the author’s conclusion that 6-OHDA causes ‘reversed quinpirole effects’ in all regions is not supported by the data.\nMinor concerns:\n1. Individual data points should be shown with the boxplots.\n2. The authors do not mention which time points were used to perform quinpirole ON and OFF comparisons to baseline, e.g., in Fig. 2b and c. Was the entire duration of the quinpirole ON taken together or a subset? Was the entire duration of the quinpirole OFF condition averaged together? If so, it should be stated, and if not, the authors should indicate these time points in the methods and figure captions, and perhaps even indicate visually on the time course graphs.\n3. The D2 receptor fluorescence in Fig. 4c and Fig. 7b is extremely dim, essentially undetectable. Additionally, the representative image for the VM in Fig. 4c appears to have the lowest D2R expression of the four subregions despite being placed in the “high D2R expression” category, so either this is a non-representative sample image or it is inappropriate to consider the VM to have high D2R expression relative to the VL and DM. Separating out the four subregions in the box plots in Fig. 4 and 7 would better show the reason for categorizing the VL/DM and DL/VM together.\n4. Figure 4e&k, and supplemental figure 3e show cumulative distribution plots for nearest neighbor distance between identified puncta. However, it is not clear how many stained slices from how many mice were used for this analysis. The authors should state their biological replicates and sample size values.\n5. A decrease in baseline PPR at striatopallidal synapses after dopamine depletion has been observed previously (Cui et al., 2016). The authors should cite this paper when they note this finding in the VL subregion (page 13, lines 380-381).\n5. The authors should explain the relevance of receptor clustering and whether the clustering differences explain subregional differences in PPR and/or alterations of PPR after dopamine depletion.\n6. The authors describe ‘cell type clarification’ conducted with imageJ in line 772 of the Methods. What does that mean? Were GPe cells stained for molecular markers known to define subpopulations (e.g., lhx6, PV, Npas1, etc)?\n7. The authors claim that the facilitating nature of the indirect pathway inputs onto the DM GPe neurons means that only robust excitatory inputs would be capable of triggering firing in GPe neurons of this region (line 520). This conclusion does not make sense. GPe neurons spontaneously fire action potentials and do not require excitatory input to fire. The indirect pathway projection neurons do not fire constantly and their signal is usually relatively brief, rather than sustained. Therefore, it is unlikely that the DM GPe would be under constant inhibition from the indirect pathway. There is no reason to think that it needs particularly robust excitatory input to fire action potentials.\n8. Though the discussion mentions that the STN connections with the GPe are topographically organized, there are other subpopulation-specific connections from the GPe to other cell types such as back to the striatum and to the dopaminergic neurons themselves (Glajch et al., 2016; Mallet et al., 2016; Evans et al., 2020) and there is a rich body of literature on GPe subpopulations (Abdi et al., 2015; Mastro et al., 2017; Abrahao and Lovinger 2018; Cui et al., 2021; Ketzef and Silberberg 2021; Courtney et al., 2023) that is largely ignored in the discussion. The similarity and potential overlap between this pinwheel organization of the GPe and the previously subdivided GPe cell types should be discussed.", "reviewer_1_attached": "The manuscript by Lee and colleagues utilizes viral tracing, IHC, imaging, slice electrophysiology and optogenetics, and D2-like receptor agonist application to examine the impact of D2/4R activation on striatopallidal transmission. The main result is that quinpirole lowers the initial probability of striatopallidal transmission at DL and VM GPe neurons through activation of pre-synaptic D2Rs and quinpirole or a D4R dopamine agonist reduces striatopallidal transmission through activation of postsynaptic D4Rs in GPe neurons throughout the nucleus. In addition, the authors provide viral tracing and IHC data supporting the idea that dopaminergic synapses are closer to striatopallidal synapses and striatopallidal D2Rs are more abundant in DL and VM GPe consistent with stronger presynaptic modulation. Overall, these findings argue for unexpected complexity in extrastriatal dopaminergic modulation mechanisms. In general, the experiments are technically well done but the use of exogenous D2/4R agonists at high concentrations leaves a key question unanswered: does native DAergic transmission also modulate striatopallidal transmission through activation of presynaptic and postsynaptic D2Rs and D4Rs respectively. Dual optogenetic stimulation of GPe DA axons and striatopallidal axons in combination with antagonist application should be used to answer this point."}, "author_response": "We thank the reviewer for their positive assessment of our study and for recognizing the technical breadth and rigor of our experiments. We also appreciate the reviewer’s thoughtful comment regarding the use of exogenous D2/4 receptor agonists. We fully agree that determining whether endogenous dopaminergic transmission engages D2- and D4-receptors to modulate striatopallidal transmission is a critical next step for understanding the physiological relevance of our findings. In our current study, however, the central aim was distinct. We sought to elucidate how activation of dopamine receptors, rather than dopamine release per se, modulates striatopallidal transmission across subregions of the GPe, which are defined by the anatomical distribution of nigropallidal dopaminergic axons.\nTo achieve stable and receptor-specific activation while avoiding the confounding effects of dopamine oxidation, we used quinpirole (QP) as a D2-like receptor agonist. This pharmacological approach enabled us to dissect receptor-specific mechanisms under tightly controlled slice conditions. Importantly, previous slice physiology studies examining striatopallidal transmission in the GPe have used comparable QP concentrations to investigate dopaminergic modulation1–3, supporting that our experimental design follows a well-established and validated framework for examining receptor-level function in low-dopamine brain regions.\nWe would also like to emphasize that, due to persistent technical limitations, the real-time, temporally precise, absolute concentration of dopamine released in brain regions with inherently low dopaminergic innervation, such as the GPe and cortex, remains largely undetermined under in vivo conditions. Moreover, partial disruption of dopaminergic boutons is unavoidable under acute slice conditions, making it technically challenging to directly assess the functional effects of native dopamine transmission in the GPe.\nIn our experiments, we directly assessed dopamine release in acute slices using fast-scan cyclic voltammetry (FSCV). Notably, previous FSCV measurements from our laboratory had already demonstrated that dopamine release in the GPe is comparable to, or slightly higher than, that in the cortex, yet markedly lower than in the striatum4. During the revision, we further confirmed this finding using a high-sensitivity FSCV system with improved signal-to-noise performance compared to conventional configurations5,6. This enhanced setup enabled reliable detection of small but consistent dopaminergic transmission in the GPe. Together, these complementary datasets validate that the GPe exhibits low yet measurable dopaminergic release, providing a robust foundation for interpreting the receptor-mediated modulation described in our study.\nImportantly, a low magnitude of dopamine release does not imply an absence of functional dopaminergic signaling. As demonstrated in cortical circuits, where dopaminergic transmission is similarly modest, neurons express multiple dopamine receptor subtypes at physiologically meaningful levels, and receptor activation has been shown to regulate synaptic, cellular, and circuit-level processes both in vivo and in vitro7–12. These observations collectively indicate that even in regions with sparse dopaminergic innervation, such as the GPe, dopamine receptors remain functionally engaged and capable of modulating local synaptic transmission. For this reason, studies investigating dopaminergic modulation in brain regions with inherently low dopamine release, including the GPe and cortex, have traditionally relied on pharmacological activation or blockade of dopamine receptors to overcome the technical limitations of directly measuring or evoking native dopamine transmission. This approach has been widely used to delineate receptor-mediated regulation of synaptic and circuit functions under conditions where endogenous release is sparse or experimentally unstable13–18. Accordingly, our use of dopamine receptor agonists in the present study follows this well-established methodological framework and is consistent with prior studies investigating dopaminergic regulation in regions with low levels of dopaminergic innervation.\nNevertheless, we greatly appreciate the reviewer’s insightful suggestion and conducted several additional experiments to directly address this point. Specifically, we performed 1) dual optogenetic stimulation, 2) low-dose quinpirole (20 nM) application, and 3) low-dose dopamine (20 nM) application experiments. The concentration of 20 nM was selected based on our FSCV measurements of dopamine release in the GPe, representing a physiologically relevant range that closely approximates endogenous dopaminergic transmission under our experimental conditions. These new experiments were designed to test whether the synaptic modulation observed in our original pharmacological data could also be reproduced under conditions mimicking endogenous dopamine release.\n1) Dual optogenetic stimulation\nWe sincerely thank the reviewer for suggesting this important experiment, which provided an opportunity to directly examine whether endogenous dopamine release can modulate striatopallidal transmission under our slice recording conditions. To address this, we performed dual optogenetic stimulation experiments in Adora2A-Cre;Ai32 mice. We bilaterally injected AAV5-hSyn-ChrimsonR-tdTomato into the SNc and electrophysiological recordings were conducted three weeks after injection (Figure 1-3).\n[...]\nIn summary, although the present dual-optogenetic experiments did not yield detectable modulation under our initial conditions, we consider it highly plausible that future refinements, such as the use of alternative opsins, stimulation frequencies, and precise temporal coordination with striatopallidal activation, will reveal native dopamine-dependent effects. Because the central focus of our study is on how dopamine receptor activation modulates striatopallidal transmission, rather than on identifying the precise release dynamics or concentration of native dopamine, we view these results as providing a valuable technical foundation rather than a limitation of our primary conclusions.\nIn parallel, to directly address the reviewer’s concern regarding physiological relevance, we conducted additional experiments using low-dose QP and low-dose dopamine application, as detailed below.\n2) Low-dose QP (20 nM) application\nTo further examine whether physiologically relevant activation of dopamine receptors could reproduce the modulation observed in our original experiments, we repeated the same recording protocol using a low concentration of QP (20 nM). Under this condition, we observed a clear and reversible reduction in oIPSC amplitude accompanied by region-specific patterns of PPR change, closely mirroring the effects obtained with higher QP concentrations. Importantly, these changes gradually returned to baseline levels upon washout of the drug, confirming that the modulation was specific and not due to rundown or instability of the recording (Extended Data Fig. 4,5). Thus, this result demonstrates that our original findings reflect genuine receptor-mediated mechanisms rather than pharmacological artifacts associated with high agonist exposure.\n3) Low-dose dopamine (20 nM) application\nWe next tested whether direct application of dopamine at a concentration comparable to the estimated physiological level could reproduce the effects observed with QP. Based on our FSCV measurements indicating ~20 nM release in the GPe, we bath-applied 20 nM dopamine while performing the same optogenetically evoked striatopallidal recordings. Under these conditions, low-dose dopamine produced a reversible reduction in oIPSC amplitude, accompanied by region-specific patterns of PPR modulation that closely mirrored the effects observed with QP. Specifically, PPR enhancement was consistently observed in the DL and VM subregions, whereas VL and DM subregions showed little or no change, precisely matching the spatial patterns identified in our original dataset. Following washout, both oIPSC amplitude and PPR returned to baseline levels, confirming that the observed effects were dopamine-specific and not due to recording drift or instability (Extended Data Fig. 6).\nTogether, these results demonstrate that physiologically relevant, low-nanomolar dopamine concentrations are sufficient to engage dopaminergic modulation in a region-dependent manner, directly supporting the conclusion that the effects described in our study reflect genuine, endogenous-range receptor activation within the GPe.\n[...]\nWe hope that these additional results clearly convey the physiological significance of our findings and fully address the reviewer’s insightful comment."}, {"round": 2, "reviewer_comments": {"reviewer_3": "Lee et al. used a combination of electrophysiological, pharmacological, imaging, and computational techniques to determine the influence of dopaminergic innervation on striatopallidal transmission. Results indicate that activation of presynaptic D2 receptors and postsynaptic D4 receptors weakens striatal inhibitory inputs to the GPe in a subregion-dependent manner. Furthermore, the authors demonstrate that dopamine depletion leads to subregion-specific presynaptic D2 receptor changes. The results further our understanding of subregional differences in the GPe and basal ganglia dysregulations after dopamine depletion. These results are exciting and useful to the basal ganglia field and the authors have addressed all concerns.\nOne minor comment: Figure 6 uses red and black to represent both ipsilateral vs contralateral and quinpirole ON vs OFF. This is confusing and a separate color should be used for one of these comparisons."}, "author_response": "We thank the reviewer for the positive evaluation of our work and for the constructive suggestion to improve the clarity of Figure 6. We agree that the concurrent use of red and black to denote both experimental conditions (ipsilateral vs. contralateral) and pharmacological states (quinpirole ON vs. OFF) may lead to ambiguity. In the revised manuscript, we have updated the color scheme to ensure a clear distinction between these variables. Specifically, the ipsilateral (6-OHDA-lesioned) group is now represented in blue, whereas the contralateral group remains in black. Red is used exclusively to indicate the quinpirole treatment state (e.g., in drug application bars and in the “QP ON” summary data). This color convention has been applied consistently across Figure 6 and the corresponding absolute values shown in Extended Data Figure 14. We have also added the following clarification to the figure legends:\n“Ipsilateral (6-OHDA) data are indicated in blue, while contralateral data are shown in black. The red bars and labels indicate the quinpirole application state.”\nWe believe that these revisions substantially improve figure readability by clearly separating pathological condition from pharmacological manipulation."}]

Decision letter