Relationship between regional gray matter volumes and dopamine D2 receptor and transporter in living human brains.

Although striatal dopamine neurotransmission is believed to be functionally linked to the formation of the corticostriatal network, there has been little evidence for this regulatory process in the human brain and its disruptions in neuropsychiatric disorders. Here, we aimed to investigate associations of striatal dopamine transporter (DAT) and D2 receptor availabilities with gray matter (GM) volumes in healthy humans. Positron emission tomography images of D2 receptor (n = 34) and DAT (n = 17) captured with the specific radioligands [11 C]raclopride and [18 F]FE-PE2I, respectively, were acquired along with T1-weighted magnetic resonance imaging data in our previous studies, and were re-analyzed in this work. We quantified the binding potentials (BPND ) of these radioligands in the limbic, executive, and sensorimotor functional subregions of the striatum. Correlations between the radioligand BPND and regional GM volume were then examined by voxel-based morphometry. In line with the functional and anatomical connectivity, [11 C]raclopride BPND in the limbic striatum was positively correlated with volumes of the uncal/parahippocampal gyrus and adjacent temporal areas. Similarly, we found positive correlations between the BPND of this radioligand in the executive striatum and volumes of the prefrontal cortices and their adjacent areas as well as between the BPND in the sensorimotor striatum and volumes of the somatosensory and supplementary motor areas. By contrast, no significant correlation was found between [18 F]FE-PE2I BPND and regional GM volumes. Our results suggest unique structural and functional corticostriatal associations involving D2 receptor in healthy humans, which might be partially independent of the nigrostriatal pathway reflected by striatal DAT.

INTRODUCTION

There is growing evidence for reciprocal and functional relationships between dopamine neurotransmission and the corticostriatal network. Striatal dopamine release modulates corticostriatal plasticity (Reynolds & Wickens, 2002), while repetitive transcranial magnetic stimulation (rTMS) of the prefrontal (Strafella, Paus, Barrett, & Dagher, 2001) and motor cortices (Strafella, Paus, Fraraccio, & Dagher, 2003) can induce dopamine release in the human striatum.

In several neuropsychiatric diseases, including schizophrenia (Abi‐Dargham et al., 2000; Caravaggio, Borlido, Wilson, & Graff‐Guerrero, 2015; Kegeles et al., 2010; Yao et al., 2013), impairments in both dopamine neurotransmission and the corticostriatal network are manifested, along with alterations in brain morphology (Honea, Crow, Passingham, & Mackay, 2005; Shepherd, Laurens, Matheson, Carr, & Green, 2012). Until now, however, only a few positron emission tomography (PET) studies have investigated the associations between brain morphology and dopaminergic statuses in humans (Caravaggio et al., 2017; Woodward et al., 2009), and their relationships in the healthy versus diseased brains remain largely unresolved. In addition, because dopamine neurons constitute cortico‐subcortical networks, rather than focusing on specific cortical or subcortical regions, it might be more beneficial to focus on a wide range of such regions to clarify the relationship between brain morphology and dopaminergic statuses in the striatum. However, these previous imaging studies were limited to intercortical or intersubcortical analysis. Further, functional and morphometric assays of the striatum are generally performed based on its anatomical subdivisions, including the caudate, putamen, and nucleus accumbens, but these structures are comprised of cytoarchitectonically undifferentiated areas (Tziortzi et al., 2014). Nonhuman nerve fiber tracing and human imaging studies have shown that the striatum could be divided into three functional subdivisions—the executive, sensorimotor, and limbic striatum—with distinct distributions of their cortical inputs onto single striatal neurons, forming monosynaptic contacts (Draganski et al., 2008; Haber, 2003; Parent & Hazrati, 1995; Wall, De La Parra, Callaway, & Kreitzer, 2013). Use of the connectivity‐based functional striatal subregions would be beneficial for a better understanding of such a relationship, which could reflect the corticostriatal network, although it should be noted that several functionally related cortical areas send partially overlapping projections to certain striatal areas (Alexander, DeLong, & Strick, 1986). Indeed, a previous study with diffusion‐weighted magnetic resonance imaging (MRI) and PET has suggested that regional differences in the striatal dopamine status could be evaluated in greater detail on the basis of connectivity‐based functional subdivision of the striatum (Tziortzi et al., 2014).

Among the components of dopamine neurotransmission, several animal studies have shown that stimulation of dopamine D2 receptors promotes the outgrowth of neurites in cerebral cortical neurons (Hasbi et al., 2009; Todd, 1992). In contrast, knockout mice of dopamine transporters (DAT) showed little morphological changes (Zhang et al., 2010). As for the relationship between dopamine D2 receptors and DATs, animal studies showed reciprocal actions between them, while there had been no comprehensive studies to examine the relationship in humans (Bolan et al., 2007; Chen et al., 2006; Courtney & Ford, 2014; Lee et al., 2007). Based on these findings, we hypothesized that brain morphology might be more related to availabilities of D2 receptors than DATs, and that there might be some relationship between availabilities of D2 receptors and DATs.

The aim of this study was (1) to examine the relationship between regional gray matter (GM) volumes and availabilities of dopamine D2 receptors and DATs in the striatal subregions divided based on the functional connectivity in healthy humans (Tziortzi et al., 2014) and (2) to investigate the relationship between availabilities of dopamine D2 receptors and those of DATs in the striatum.

MATERIALS AND METHODS

Subjects

We collected data from neuroimaging datasets in our two previous clinical studies ([UMIN000008232] (Kimura et al., 2017), [UMIN000007240]), which had been registered in the University Hospital Medical Information Network Clinical Trials Registry. The participants were 34 nonsmoking male volunteers (age, 23 ± 1.9 years; body mass index, 20.9 ± 1.9 kg/m2; mean ± SD). By a board‐certified psychiatrist, we confirmed that all subjects were free of both current and past medical and neuropsychiatric illnesses based on their medical histories and physical examinations, and also of current use of psychoactive drug/medication.

This study was approved by the Institutional Review Board of the National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan, and was performed in accordance with the ethical standards established in the 1964 Declaration of Helsinki and its later amendments. Written informed consent was obtained from all subjects before their inclusion in the study.

PET procedures

All subjects underwent a PET scan with [11C]raclopride, a D2/3 receptor radioligand. Among them, 17 individuals (age, 22 ± 0.9 years) also completed a PET scan with [18F]FE‐PE2I, a DAT radioligand. Injection doses of [11C]raclopride and [18F]FE‐PE2I were 222.1 ± 15.5 MBq and 185.3 ± 20.7 MBq, respectively, and molar activities of [11C]raclopride and [18F]FE‐PE2I were 210.0 ± 61.7 GBq/μmol and 410.5 ± 319.1 GBq/μmol, respectively. With regard to the 17 subjects undergoing both the PET scans with [11C]raclopride and [18F]FE‐PE2I, [18F]FE‐PE2I PET scan was begun 2 hr after the start of [11C]raclopride PET. PET images were acquired using a PET camera (SET‐3000GCT/X, Shimadzu, Kyoto, Japan), with the imaging session consisting of 35 frames of increasing duration from 30 s to 5 min over 60 min for [11C]raclopride and 38 frames over 90 min for [18F]FE‐PE2I. Scatter correction was performed by a hybrid scatter correction method based on acquisition with dual‐energy window setting (Ishikawa et al., 2005). A 4‐min transmission scan using a 137Cs line source was obtained to correct for attenuation.

MRI procedures and preprocessing

All MRI scans were performed with a 3‐T MRI scanner (MAGNETOM Verio, Siemens, Germany). 3D volumetric acquisition of a T1‐weighted gradient echo sequence produced a gapless series of thin sagittal sections. The scan parameters for our participants were either of the following sets: (1) TE, 9.2 ms; TR, 21 ms; flip angle, 30°; and slice thickness, 1 mm (n = 17; subjects who completed both [11C]raclopride and [18F]FE‐PE2I PET; UMIN000008232; Kimura et al., 2017); or (2) TE, 3.43 ms; TR, 2300 ms; flip angle, 30°; and slice thickness, 1 mm (n = 17; subjects who completed [11C]raclopride PET only) (UMIN000007240).

MRI data were processed and analyzed using statistical parametric mapping (SPM12, Wellcome Trust Centre for Neuroimaging, London, UK) software, specifically using Diffeomorphic Anatomical Registration Through Exponentiated Lie algebra (DARTEL) toolbox running on Matlab R2018b (MathWorks, MA; Ashburner, 2007). In the segmentation procedure, brain structures were classified into GM, white matter (WM), and cerebrospinal fluid (CSF), which were resliced into 1.5 × 1.5 × 1.5 mm voxels. We created a customized template from the images of all participants. The GM images were spatially normalized into the standardized Montreal Neurological Institute (MNI) 152 brain template. The voxel values of segmented and normalized GM images were modulated by the Jacobian determinants obtained from a nonlinear normalization step. In the smoothing procedure, a Gaussian kernels filter was used to smoothen normalized images. The kernel size of the Gaussian filter was set to 8 mm in full‐width at half‐maximum (FWHM).

Quantification of PET images

PET data processing was conducted using PMOD 3.8 (PMOD Technologies Ltd., Zurich, Switzerland).

All PET images were reconstructed using the filtered back‐projection method (Gaussian filter, kernel 5 mm; reconstructed in‐plane resolution 7.5 mm at FWHM; voxel size 2 × 2 × 2.6 mm). Motion‐corrected PET images were co‐registered to corresponding individual MR images. All PET images were spatially normalized to MNI152 standard space, based on parameters for the transformation of individual MR images into the template estimated by DARTEL SPM12. The striatal and cerebellar ROIs along with normalized MRI and PET images of a single subject are illustrated in Figure S1.

Quantitative analysis was then performed by applying a simplified reference tissue model (SRTM; Alakurtti et al., 2015; Boileau et al., 2013; Lammertsma & Hume, 1996; N. B. Urban et al., 2012) to the time course of radioactivity concentrations in the striatal subregions using the cerebellar cortex as reference tissue. Availabilities of D2 receptors and DATs were quantified as binding potentials relative to the nondisplaceable tissue (BP ND) of [11C]raclopride and [18F]FE‐PE2I, respectively. A connectivity‐based probabilistic atlas of the striatum (Tziortzi et al., 2014) was applied to the spatially normalized PET images to determine BP ND values in the limbic, executive, and sensorimotor striatal subregions. We used the atlas of the cerebellar lobules in MNI152 standard space (Diedrichsen, Balsters, Flavell, Cussans, & Ramnani, 2009).

Additionally, we performed partial volume correction (PVC) using the Müller‐Gärtner approach (Müller‐Gärtner et al., 1992), as in previous studies (Ito et al., 2014; Mecca et al., 2018; Mecca et al., 2020). For each dynamic PET frame, GM voxels were corrected for spill‐in and spill‐out of activity, assuming that activity in CSF was 0 and WM activity was uniform and was estimated from each image time frame.

Data analysis

Correlations between local GM volume and BP ND of [11C]raclopride and [18F]FE‐PE2I

We investigated correlations between the local GM volume and BP ND of [11C]raclopride and [18F]FE‐PE2I in the three striatal subregions while controlling for age, total brain volume, and MRI parameters, using voxel‐based morphometry (VBM) implemented in SPM12 running on Matlab R2018b (J. Ashburner & Friston, 2000). The statistical significance threshold for VBM was set at p < .001/3 at peak levels, which was corrected for the three striatal subregions. We performed VBM analysis because VBM allows the investigation of GM regions of the whole brain without bias, and thus might be more suitable for exploratory studies.

We conducted the following additional analyses to examine whether the associations between availabilities of D2 receptors and brain morphology were explained by DAT or not. First, the regional GM volume data (eigenvariates) were extracted from the above‐mentioned clusters significantly correlated with the BP ND values of [11C]raclopride in the 34 subjects. Namely, from our VBM results, we extracted (1) eigenvariates from clusters significantly correlated with the limbic striatal BP ND of [11C]raclopride, (2) eigenvariates from clusters significantly correlated with the executive striatal BP ND of [11C]raclopride, and (3) eigenvariates from clusters significantly correlated with the sensorimotor striatal BP ND of [11C]raclopride, respectively. We performed a correlational analysis between the BP ND values of [11C]raclopride and the regional GM volume data (eigenvariates) for each striatal subregion, respectively, in (1) all subjects (n = 34), and (2) subjects undergoing both [11C]raclopride and [18F]FE‐PE2I PET scans (n = 17), respectively. Next, in these 17 subjects, we performed a partial correlational analysis for the above correlations while controlling for the BP ND values of [18F]FE‐PE2I. Further, we performed a correlational analysis between the BP ND values of [18F]FE‐PE2I and the regional GM volume data (eigenvariates) for each striatal subregion in subjects undergoing both [11C]raclopride and [18F]FE‐PE2I PET scans (n = 17). The statistical significance threshold was set at p < .05/3 in these analyses. Data were analyzed by using the Statistical Package for Social Sciences (SPSS) version 25 (SPSS, Inc., Chicago, IL).

Correlations between the BP ND of [11C]raclopride and [18F]FE‐PE2I

We examined correlations between the BP ND of [11C]raclopride and [18F]FE‐PE2I in each striatal subregion by correlational analysis, with a statistical significance threshold of p < .05/3. Data were analyzed by using SPSS.

RESULTS

Correlations between local GM volume and BP ND of [11C]raclopride

We found significant positive correlations of [11C]raclopride BP ND in the limbic striatum with GM volumes in a limbic area, including the uncal/parahippocampal cortex [Brodmann's area (BA) 36], and adjacent temporal cortices (BA 20, 21, 38), along with the declive of the cerebellum (Table 1 and Figure 1). Likewise, a significant positive correlation was observed between [11C]raclopride BP ND in the executive striatum and GM volumes in regions associated with executive functions, such as prefrontal (BA 8, 9, 10) cortices, and an area adjacent to the prefrontal cortex (BA 6, 32), along with a parietal cortical region (BA 40) (Table 1 and Figure 1b). Moreover, [11C]raclopride BP ND in the sensorimotor striatum was significantly and positively correlated with GM volumes in regions associated with sensorimotor functions, such as the supplemental motor (BA 6) and somatosensory (BA 40) cortices and an area adjacent to the premotor cortex (BA 8, 9), as well as the frontal pole (BA 10) and lingual (BA 18) gyri (Table 1 and Figure 1c).

TABLE 1

Local maxima of positive correlations between [11C]raclopride BP ND in the subregion of the striatum and regional GM volumes

Subregion of the striatum	Brain region	Talairach coordinates			p‐value at the peak level		p‐value at the cluster level
		X	Y	Z	Uncorrected	FWE	Uncorrected
Limbic	Right middle temporal gyrus (BA 21)	42	6	−36	<.00033	.034	.014	421
	Left inferior temporal gyrus (BA 20)	−48	−4	−27	<.00033	.352	.149	126
	Left cerebellum, posterior lobe, declive	−28	−78	−22	<.00033	.396	.026	336
	Right limbic lobe, uncus (BA 36)	26	−10	−33	<.00033	.516	.161	118
	Left superior temporal gyrus (BA 38)	−30	6	−39	<.00033	.64	.005	581
Executive	Left medial frontal gyrus (BA 9)	−16	32	27	<.00033	.029	.018	383
	Right medial frontal gyrus (BA 6)	14	−4	54	<.00033	.214	.307	61
	Right medial frontal gyrus (BA 10)	20	46	3	<.00033	.238	.249	78
	Right inferior parietal lobule (BA 40)	40	−30	48	<.00033	.608	.025	339
	Right inferior parietal lobule (BA 40)	51	−57	51	<.00033	.688	.243	80
	Left anterior cingulate (BA 32)	−20	44	8	<.00033	.764	.292	65
	Left postcentral gyrus (BA 2)	−40	−20	32	<.00033	.831	.285	67
	Left medial frontal gyrus (BA 8)	−9	33	45	<.00033	.881	.337	54
Sensorimotor	Right medial frontal gyrus (BA 6)	12	−18	57	<.00033	.195	.069	208
	Right medial frontal gyrus (BA 10)	18	46	4	<.00033	.241	.337	54
	Left lingual gyrus (BA 18)	−14	−74	−6	<.00033	.413	.167	114
	Left medial frontal gyrus (BA 9)	−18	30	27	<.00033	.502	.114	152
	Right medial frontal gyrus (BA 8)	12	38	40	<.00033	.598	.274	70
	Right postcentral gyrus (BA 40)	42	−30	50	<.00033	.656	.007	520

Note: Statistical significance threshold for VBM was set as p < .001/3 (uncorrected) at the peak level represented in bold. Voxel size 1.5 × 1.5 × 1.5 mm2. Extent threshold: 50 voxels.

Abbreviations: BA, Brodmann's area; FWE, family‐wise error.

FIGURE 1

(a) Regions of gray matter positively correlated with [11C]raclopride BP ND in the limbic striatum. (b) Regions of gray matter positively correlated with [11C]raclopride BP ND in the executive striatum. (c) Regions of gray matter positively correlated with [11C]raclopride BP ND in the sensorimotor striatum. The statistical significance threshold was set at p < .001/3 (uncorrected) at the peak levels, with a 50‐voxel extent threshold

Results after applying PVC were as follows: there were positive correlations between (1) [11C]raclopride BP ND in the limbic striatum and GM volumes in temporal cortices adjacent to the limbic area (BA 20, 38), (2) [11C]raclopride BP ND in the executive striatum and GM volumes in medial frontal (BA 9) and postcentral (BA 3) cortices, along with inferior temporal (BA 19) cortices, and (3) [11C]raclopride BP ND in the sensorimotor striatum and GM volumes in regions associated with sensorimotor functions, such as postcentral (BA 3) cortices, as well as the cingulate (BA 24) and medial frontal (BA 10) cortices.

In all subjects, significant positive correlations were found between the BP ND values of [11C]raclopride and eigenvariates for the limbic (p = .011, Pearson's r = .43), executive (p = .001, r = .53), and sensorimotor (p = .001, r = .54) subregions of the striatum, respectively (Figure 2).

FIGURE 2

(a) Scatter plot of [11C]raclopride BP ND in the limbic striatum against regional gray matter (GM) volume data (eigenvariates; n = 34). The GM volume data (eigenvariates) were extracted from the clusters significantly correlated with the limbic striatal BP ND of [11C]raclopride in our VBM results shown in Figure 1a. (b) Scatter plot of [11C]raclopride BP ND in the executive striatum against regional GM volume data (eigenvariates; n = 34). The GM volume data (eigenvariates) were extracted from the clusters significantly correlated with the executive striatal BP ND of [11C]raclopride in our VBM results shown in Figure 1b. (c) Scatter plot of [11C]raclopride BP ND in the sensorimotor striatum against regional GM volume data (eigenvariates) (n = 34). The GM volume data (eigenvariates) were extracted from the clusters significantly correlated with the sensorimotor striatal BP ND of [11C]raclopride in our VBM results shown in Figure 1c

In the 17 subjects undergoing PET scans with both [11C]raclopride and [18F]FE‐PE2I, significant positive correlations were found between the BP ND values of [11C]raclopride and the eigenvariates for the executive (p = .003, r = .67) and sensorimotor (p = .007, r = .62) subregions of the striatum, respectively, while a correlation between these parameters for the limbic striatum showed a trend toward significance (p = .116, r = .40) (Figure 2).

Partial correlational analyses also revealed significant positive correlations between the BP ND values of [11C]raclopride and the eigenvariates for the executive (p = .001, r = .75) and sensorimotor (p = .006, r = .66) subregions of the striatum, respectively, while a correlation between these parameters for the limbic striatum showed a trend toward significance (p = .067, r = .47).

On the other hand, there were no significant correlations between the BP ND values of [18F]FE‐PE2I and the eigenvariates for any of the striatal subregions (Figure 3).

FIGURE 3

(a) Scatter plot of [18F]FE‐PE2I BP ND in the limbic striatum against regional gray matter (GM) volume data (eigenvariates; n = 34). The GM volume data (eigenvariates) were extracted from the clusters significantly correlated with the limbic striatal BP ND of [11C]raclopride in our VBM results shown in Figure 1. (b) Scatter plot of [18F]FE‐PE2I BP ND in the executive striatum against regional GM volume data (eigenvariates; n = 34). The GM volume data (eigenvariates) were extracted from the clusters significantly correlated with the executive striatal BP ND of [11C]raclopride in our VBM results shown in Figure 1b. (c) Scatter plot of [18F]FE‐PE2I BP ND in the sensorimotor striatum against regional GM volume data (eigenvariates; n = 34). The GM volume data (eigenvariates) were extracted from the clusters significantly correlated with the sensorimotor striatal BP ND of [11C]raclopride in our VBM results shown in Figure 1c

Correlations between local GM volume and BP ND of [18F]FE‐PE2I

By contrast to the above VBM results using [11C]raclopride BP ND, no significant correlation was found between regional GM volume and BP ND of [18F]FE‐PE2I.

Correlations between the BP ND of [11C]raclopride and [18F]FE‐PE2I

There were significant positive correlations between the BP ND values of [11C]raclopride and of [18F]FE‐PE2I in the executive (p = .005, r = .65) and sensorimotor (p = .014, r = .58) subregions of the striatum, while no significant correlation was found between these parameters in the limbic striatum (p = .18, r = .34).

DISCUSSION

We have demonstrated positive correlations between dopamine D2/3 receptor radioligand BP ND in the functional subregions of the striatum and the GM volumes of regions that could be functionally and anatomically connected to each of these striatal subdomains. Meanwhile, no marked correlations were observed between DAT radioligand BP ND and regional GM volumes. Before and after applying the PVC, generally there were no noticeable differences in the results (although slight differences were found for the executive striatum).

To date, only a few studies have investigated the relationship between brain morphology and the dopamine system in healthy humans. A previous PET study has reported associations between cortical thickness and dopamine release in striatal subregions; greater amphetamine‐induced changes in [11C]raclopride BP ND were observed in the ventral limbic striatum, and they were associated with thinner frontal cortices (Jaworska et al., 2017). With regard to the relationship between brain morphology and D2 receptor availability, there were only two studies, and the findings were inconsistent (Caravaggio et al., 2017; Woodward et al., 2009). Namely, one of these two PET studies with [18F]fallypride has demonstrated a positive intraregional correlation between D2/3 receptor availability and the GM volume within the caudate, thalamus, and amygdala in healthy human brains (Woodward et al., 2009). The other exploratory clinical PET study with two D2/3 receptor radioligands, [11C]raclopride and [11C]‐(+)‐PHNO, in healthy individuals reported that BP ND of [11C]‐(+)‐PHNO but not [11C]raclopride was positively correlated with the local volume within anatomical striatal subregions except for the putamen (Caravaggio et al., 2017). Unlike those within‐region analyses, the present work explored the relationship between the morphology across GM regions and the striatal dopamine system in healthy humans. Furthermore, we focused on the connections from cortical inputs and functionally distinct striatal subdivisions, leading to revelation of the associations between the morphology and dopaminergic components via the corticostriatal circuits. We did not find any significant associations between GM volumes within the striatum and D2 receptor availabilities, unlike those previous studies (Caravaggio et al., 2017; Woodward et al., 2009). Possible interpretations might be due to the difference in radioligands, that is, [11C]raclopride in Caravaggio et al. and our study vs. [11C]‐(+)‐PHNO in Caravaggio et al. and [18F]fallypride in Woodward et al: differences in selectivity for D2 versus D3 receptors or in affinity for endogenous dopamine among these radioligands (Gallezot et al., 2012; Mukherjee et al., 2002). Otherwise, it might be due to differences in demographic data (e.g., male ratio: 100% in our study, 53% in Woodward et al., 63% in Caravaggio et al.; age: 23 ± 1.9 years in our study, 24 ± 5.5 in Woodward et al., 39 ± 14.5 for [11C]raclopride and 39 ± 14.6 for [18F]fallypride in Caravaggio et al.). In the current study, we targeted the GM volume among several morphometric measures. As the present study was for exploratory research, we did not investigate the relationship between these dopamine neurotransmissions and functional/structural connectivity. Future studies will be needed to examine the relationship between dopamine neurotransmission, cortical thickness/surface area/volume, and functional/structural connectivity in greater detail.

In consideration of the availabilities of D2 and D3 receptors and affinities of [11C]raclopride for these target molecules, it is conceivable that PET data with this radioligand is primarily indicative of the D2 receptor availability in the striatum. Hence, the positive correlation between [11C]raclopride BP ND in the limbic, executive, and sensorimotor striatal subregions and GM volumes of functionally connected cortices could imply the roles of dopamine as a morphogen in the formation and preservation of the cortical networks mediated by striatal D2 receptors. Indeed, a previous in‐vitro study demonstrated that a D2 receptor agonist stimulated the outgrowth of neurites in cerebral cortical neurons, whereas a D2 receptor antagonist abolished it (Todd, 1992). Therefore, D2 receptors on presynaptic terminals of the cortical inputs in the striatum are likely to retrogradely elicit the generation and extension of neuritic processes, resulting in an enlarged cortical morphology. A combined in‐vitro neuronal culture and in‐vivo rat study also documented that the stimulation of dopamine D1‐D2 receptor heteromers increased brain‐derived neurotrophic factor (BDNF) production and neuronal growth in the striatum (Hasbi et al., 2009), raising the possibility that this dopamine‐induced BDNF increment backwardly promotes the outgrowth of neurites in cortical neurons constituting the corticostriatal pathway. Because the current study employed a cross‐sectional design, a longitudinal morphometric assay during treatment with a D2 receptor agonist would be necessary for drawing a more decisive conclusion for these regulatory systems. Such investigations should preferably be conducted in healthy subjects, but there would be difficulties in the long‐term administration of a D2 blocker in such individuals.

One of the possible explanations for the present results might be that the number of cortical neurons projecting to the striatum determines the density of D2 receptors on their presynaptic terminals and the opposite postsynaptic compartments of striatal projection neurons. The nerve fiber and synaptic densities in the corticostriatal tract may regulate the resilience of this network, although the striatal dopaminergic tone, which is functionally linked to the balance between presynaptic and postsynaptic D2 receptors, could not greatly fluctuate. However, interpretation of our results should be done with caution, as [11C]raclopride BP ND does not solely reflect D2 receptor density, but is also influenced by other factors such as endogenous dopamine levels and receptor conformation. Our results of partial correlational analyses suggested that the association between brain morphology and D2 receptors was not explained by DAT availability. The correlation between [11C]raclopride BP ND in the limbic striatal subregion and eigenvariates in the 17 subjects remained at a trend level significance, presumably due to the small sample size, as the r value was similar to the analysis of the whole sample (0.40 in 17 subjects vs. 0.43 in 34 subjects).

In contrast to D2 receptors, we could not find significant correlations of DAT availability with the GM volumes of any brain regions. DAT availability is believed to be associated with the density of the nigrostriatal dopaminergic terminals (Hersch, Yi, Heilman, Edwards, & Levey, 1997; Kimmel, Joyce, Carroll, & Kuhar, 2001), but baseline concentrations of synaptically released dopamine, which could act on the corticostriatal nerves as a morphogen, may be stabilized in a manner independent of this density in a healthy, homeostatic condition. In a pathological circumstance causing profound changes in DAT availability, abnormalities of tonic dopamine levels at the synaptic cleft may occur, affecting the morphology of the connected cortical areas. In fact, accumulating evidence suggests that reduced DAT radioligand binding is cross‐sectionally and longitudinally associated with cortical atrophy in Parkinson's disease (PD; Sampedro, Marin‐Lahoz, Martinez‐Horta, Pagonabarraga, & Kulisevsky, 2019; Ye et al., 2018). The underlying condition of cortical atrophy in PD is considered to be as follows. First, impairments of the nigrostriatal pathway give rise to a loss of presynaptic terminals releasing dopamine. Then, the DAT density in the striatum declines, leading to a decrement of the activation of D2 receptors and spoiling the corticostriatal circuits (Calabresi, Pisani, Centonze, & Bernardi, 1997; Kreitzer & Malenka, 2007; Petzinger et al., 2013; Picconi et al., 2003; Shen, Flajolet, Greengard, & Surmeier, 2008).

The current study is the first to assess the relationships between D2 receptors and DATs in functional striatal subdivisions. We found positive correlations between the availabilities of these two components in the executive and sensorimotor striatal subregions, presumably reflecting a coupled change in the availabilities of presynaptic and postsynaptic terminals derived from the corticostriatal and nigrostriatal circuit neurons. Such coupling intensity could have diversity among the three subregions, but these data should be considered as being preliminary in light of the relatively small sample size in the present assays. Although the mechanism underlying the reciprocal action between D2 receptor and DAT is not well clarified, some relevant findings have been reported, as several in vitro and in vivo studies have revealed that D2 receptor activation could increase DAT mediated DA clearance and DAT cell‐surface expression (Bolan et al., 2007; Cass & Gerhardt, 1994; Mayfield & Zahniser, 2001; Meiergerd, Patterson, & Schenk, 1993); in a rat study, D2 agonist and antagonist decreased and increased the half‐life of DAT in the striatum, respectively, suggesting that dopamine might have influenced DAT turnover through D2 receptor (Kimmel et al., 2001); another rat study showed that DAT might be regulated by D2 receptor through a direct protein–protein interaction being independent of D2 receptor activation (Lee et al., 2007). Conversely, accumulating findings of in vitro studies suggest that DAT regulates reuptake, spillover, and diffusion of extracellular dopamine, resulting in activation of D2 receptor (Chen et al., 2006; Courtney & Ford, 2014).

Our results showed that [11C]raclopride BP ND in each striatal subregion was significantly correlated with GM volumes in regions associated with each function (i.e., limbic, executive, and sensorimotor) and those adjacent areas. The parahippocampal gyrus, being correlated with [11C]raclopride BP ND in the limbic striatal subregion, is considered to be the primary hub of the default mode network in the medial temporal lobe memory system during resting state (Ward et al., 2014). The temporal cortices adjacent to the limbic system have been reported to have a connection with the ventral‐medial anterior caudate in nonhuman primates, although the connection between the temporal lobe and striatum was limited in Tziortzi et al.'s diffusion‐weighted MRI study (Selemon & Goldman‐Rakic, 1985; Tziortzi et al., 2014). The prefrontal cortex, being correlated with [11C]raclopride BP ND values in the limbic striatal subregion, is known to play a central role in organizing and controlling goal‐directed thought and behavior (Szczepanski & Knight, 2014). The supplementary motor cortices and somatosensory cortices, being correlated with [11C]raclopride BP ND values in the sensorimotor striatal subregion, are thought to be crucial in voluntary movement and linking between sensory processing and movement production, respectively (Borich, Brodie, Gray, Ionta, & Boyd, 2015; Nachev, Kennard, & Husain, 2008). Our results suggest that dopamine D2 receptors in these striatal subregions might be involved in the functioning of these brain regions, respectively. On the other hand, [11C]raclopride BP ND values in each of the striatal subregions were also correlated with regions overlapping with other subregions. This might reflect integrating information between functions with overlapping projections throughout the striatum that enables reward‐based and goal‐directed behaviors, as indicated previously (Tziortzi et al., 2014). The correlations between BP ND and the eigenvariates were not significantly different among the three subregions when comparing the z‐transformed correlation coefficients by two‐tailed t‐tests (Pearson's r value range, .43–.54; p value range, .57–.96 in the 34 subjects), suggesting that the strength of associations between striatal dopamine D2 availability and related brain regions might not be markedly different among them. However, to clarify this issue in greater detail, further neuroimaging studies combined with functional/structural connectivity measures will be necessary.

Along with novel findings and implications, there are also some possible limitations in this study. First, we investigated correlations rather than causal relationships between dopamine neurotransmission and brain morphology. Second, we should be careful in interpreting the results because of the small sample size. Third, although the Müller‐Gärtner approach corrects the effects of spill‐in and spill‐out of radioactivity between GM and WM and decreases the influence of striatal brain volume on measured uptake, and our results with PVC are generally consistent with the results without PVC, the Müller‐Gärtner approach could not correct the effects of spill‐in and spill‐out within the three striatal subregions. Fourth, we did not perform a drug screening test on the day of PET acquisition to completely exclude the use of psychoactive substances that can influence D2 receptor availabilities, although the absence of past and current drug use was confirmed by an interview by a board‐certified psychiatrist. Indeed, intake of some psychoactive substances, such as alcohol and caffeine, can influence D2 receptor availabilities (Nina BL Urban et al., 2010; Volkow et al., 2015). Finally, the limited age range and sex of the participants impeded assessments of the effect of these two parameters. Accordingly, our results should be cautiously interpreted in view of these technical issues.

In conclusion, our results demonstrated differential involvements of DATs and D2 receptors in the links between cortical morphology and the striatal dopaminergic system via the functional connections. The current findings also suggest unique structural and functional corticostriatal associations in healthy humans, which might be somewhat independent of the nigrostriatal pathway. Similar PET and MRI approaches will provide insights into the implication of the dopamine transmission in the structures of connected regions in neuropsychiatric disorders. It should be of particular significance to conduct these assays in drug‐naïve patients with schizophrenia, since aberrant GM volumes and striatal dopaminergic statuses have been reported in this illness (Haijma et al., 2013; Howes et al., 2012).

CONFLICT OF INTERESTS

The authors have no conflicts of interest directly relevant to the content of this article.

AUTHOR CONTRIBUTIONS

Manabu Kubota conceived the original idea. Hironobu Fujiwara, Yasuyuki Kimura, and Hiroshi Ito carried out the experiments. Shin Kurose and Manabu Kubota analyzed the data and wrote the first draft. Shin Kurose, Manabu Kubota, Keisuke Takahata, Yasuharu Yamamoto, Hiroyoshi Takeuchi, and Makoto Higuchi contributed to the interpretation of the results. Makoto Higuchi supervised the project. All authors have made substantial intellectual contribution to the work and approved the final manuscript.

FIGURE S1 Striatal and cerebellum ROIs used in our analysis. ROIs are shown along with single subject's MRI image and summed PET image of [11C]raclopride normalized with DARTEL algorithm

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