In the present paper we applied the PCA strategy to reveal the spatial organization of D2-like BPND in the human brain. When multiple regions share high positive loadings on a given component, the loadings (and the corresponding correlations of ROIs) suggest there is a common influence explaining a portion of the variance. However, the data do not clarify the source of this influence, which could reflect fundamental biological processes, a methodological source of variance in the measurement of BPND, or both. In contrast, to the extent that areas show separate patterns of loadings, it suggests that the variances are caused by different influences, be they functional or methodological. As such, the results of the present analyses help identify which organizational features need to be explained, and may suggest hypotheses regarding the functional or methodological influences that cause the spatial organization of D2-like BPND. In the discussion that follows we highlight the core organizational features that need to be explained, with the hope that it will lead to experimentation to directly test potential sources of influence across brain regions. We also note some critical methodological variables that may influence the observed patterns of BPND across subjects.
A key conclusion that arises from present analyses is that we cannot treat D2-like BPND
measured only in the striatum as a global index of D2-like receptor status throughout the whole brain. The cortex and striatum largely loaded on separate components, and only 10% of the variance in overall cortical D2-like BPND
was explained by striatal D2-like BPND
. The relative dissociation between cortical and striatal regions appears to at least grossly conform to the classic distinction between nigrostriatal and mesocortical DA systems, and suggests distinct regulatory influences on the target D2-like receptors of these two systems. Several factors may contribute to this differential regulation including differences in the transmission and termination of DA. For instance, DA released into the striatum is rapidly removed from the synapse, whereas in cortex, the low levels of DA transporter allow released DA to remain in the synapse for significantly longer periods of time (Seamans and Yang, 2004
). Evidence for the separate regulation of cortical and striatal binding has also been observed for D1 receptor BPND
(Abi-Dargham et al., 2002
), which suggests that the observed independence of striatal and extrastriatal binding is a general feature of the DA system.
A methodological caveat is necessary in interpreting data on the modest relationship of striatal and extrastriatal BPND
. Extracellular levels of DA are substantially higher in the striatum than in the cortex (Moghaddam et al., 1993
), and this may differentially impact measures of receptor availability. The BPND
of benzamides such as [18
F]fallypride are affected by endogenous DA levels (Riccardi et al. 2005
). Because of this, BPND
is interpreted as a measure of receptor availability, rather than absolute receptor density. It has been argued that endogenous DA leads to an average underestimation of BPND
of 20-30% for D2 radioligands in the striatum (Laruelle, 2000
)(note: given existing data, [18F]fallypride is predicted to be slightly less susceptible to this underestimation than other striatal ligands, such as [11
C]raclopride). Endogenous DA appears to exert substantially less impact on cortical BPND
, as demonstrated by the higher stability of cortical BPND
in the face of pharmacological manipulations (Cropley et al., 2008
; Okauchi et al., 2001
; Riccardi et al., 2005
). Given the observation of different sensitivity to endogenous DA, as well as differences in DA cell firing, metabolism and turnover across nigrostriatal, mesolimbic, and mesocortical regions (Bannon & Roth, 1983
), it is possible that some of the observed differences in striatal vs. extrastriatal BPND
could arise from regional differences in extracellular DA or the regulation of DA release as opposed to specific differences in receptor density or affinity. Unfortunately, at present it is not possible to fully tease apart the differential contributions to observed BPND
using in-vivo PET. It may, however, be possible with animal studies and human post-mortem studies to determine the relative contribution of receptor concentration, receptor affinity, and presynaptic or metabolic effects on these regional patterns of receptor availability.
The PCA of z-transformed data identified specific areas of cortex that show unique associations with striatal BPND
. Of note, Component #2 revealed an inverse association between BPND
in ventral and lateral temporal cortex and the striatum after controlling for the first (cortical) component. Critically, this negative relationship was only clearly visible after controlling for the first (largely cortical) component. This suggests that there is an inverse interaction between D2-like BPND
in the temporal cortex and striatum, but that it may be obscured unless one controls for other global influences on D2-like receptor availability. A more modest inverse relationship was also observable along the medial frontal wall (particularly ventrally). While preclinical models have described inverse relations between DA functioning in frontal and striatal regions (Deutch, 1992
; Pycock et al., 1980
; Weinberger, 1987
), far less attention has been paid to the temporal cortex. One exception is medial temporal regions, which have been found to regulate aspects of striatal DA functioning (Heinz et al. 1999
; Louilot and Choulli, 1997
). However, to our knowledge, no existing data specifically addresses cross-regulation between DA receptor functioning in the striatum and more lateral temporal cortical areas
A striking aspect of this study was the extent to which areas that are in close proximity often showed very different patterns of component loadings. For instance, subcortical medial temporal structures showed substantially different relationships than more lateral temporal areas, potentially reflecting a mesolimbic vs. mesocortical projection system. The separation between different parts of the thalamus was particularly striking, with more medial/midline and lateral thalamic regions demonstrating opposite loadings on some components. The thalamus shows substantial nuclei-specific heterogeneity in the DA cell groups from which it receives projections, and in its level of D2, D3 and DA transporter expression (Garcia-Cabezas et al., 2007
; Rieck et al., 2004
; Sanchez-Gonzalez et al., 2005
). There are marked differences in BPND
levels across thalamic nuclei, with the highest levels corresponding to the rostral half of the dorsal midline thalamic nuclei (including paraventricular and parataenial nuclei) and lower levels in more lateral structures (Rieck et al., 2004
). The PCA appears to be capturing this distinction, suggesting that the midline thalamic nuclei with higher BPND
are regulated differently than the more laterally located nuclei with lower BPND
. The observation of nuclei specific influences of D2-like binding is of particular interest for schizophrenia, in that recent studies have indicated the presence of lowered [18
in schizophrenic patients (Buchsbaum et al., 2006
; Kessler et al., 2009
). The present data suggest the potential utility of distinctly analyzing medial and lateral thalamic regions in future studies of thalamic DA. Indeed, the data suggest caution in applying a thalamic-wide ROI, which may obscure regionally- or nuclei-specific effects.
Whereas different parts of the thalamus showed dissociable loadings, the striatum (as well as the globus pallidum) showed an extremely homogenous pattern of component loadings, with almost the entire variance accounted for by a single component in the raw analysis of BPND
. An important methodological factor that could increase homogeneity in this area is contamination of counts from neighboring areas of the striatum. However, the level of observed covariance between dorsal (caudate/putamen, or associative/sensorimotor) and ventral striatal regions far exceeds the amount of covariance that would be predicted simply based on a contamination of counts across striatal regions (Mawlawi et al., 2001
). We note in this regard, that we applied no additional smoothing to the data, and provided a large gap between ventral striatum and caudate and putamen ROIs in order to minimize the contribution of neighboring voxels to both ROIs. Moreover, the homogenous component loadings spread across relatively distal areas of the striatum (areas that are 30 mm distant still show similar loadings). This contrasts with the thalamus, where areas that are only a few mm apart show dramatically different loadings.
The homogenous loadings of the striatum suggest a common influence over individual differences in D2-like BPND that cuts across different functional zones of the striatum. Indeed, although the ventral striatum (nucleus accumbens) is classically treated as part of the mesolimbic system rather than the nigrostriatal system, its pattern of loadings and correlations converged with the rest of the striatum, rather than with limbic areas. As such, individual differences in D2-like receptor availability are likely to produce similar impacts across a number of affective, cognitive and motoric domains. This may lead to the common expression of certain cognitive, affective or behavioral traits, despite each of the traits reliance on circuits involving different striatal regions.
The homogenous striatal loadings also imply that, at least in healthy individuals, variables that correlate with baseline D2-like BPND in one portion of the striatum will typically correlate with BPND in all areas of the striatum. This conclusion does not exclude the possibility that some areas of the striatum will show greater associations with a given trait than another region. However, true dissociations (as demonstrated by tests for significant differences between correlations) in the correlates of D2-like BPND across striatal regions are unlikely. Rather, correlations with different ROI regions are likely to all be in a similar direction, although some may reach an arbitrary level of statistical significance, while others fall below this significance level. For example, in a recent study by Volkow et al. (2009) in which striatal [11C] raclopride binding was correlated with prefrontal and cingulate glucose metabolism in subjects with a positive history of alcoholism, correlations with the ventral striatal ROIs were always in the same direction as those for the dorsal striatal ROIs. In all cases where there was a highly significant correlation in a dorsal striatal ROI, there was also a significant correlation with the ventral striatal ROI. Only when effect sizes were more modest for the dorsal striatal ROIs did the ventral striatal ROI fail to produce similarly statistically significant results, but this may be attributed to statistical power issues, and the arbitrary nature of a p < 0.05 cutoff, rather than a dissociation, since the correlations for the dorsal and the ventral striatal ROI were not significantly different.
The observed homogeneity in individual differences in striatal D2-like BPND
also does not exclude regional variation in other measures of DA functioning (such as synthesis or release). Indeed, pharmacological studies of DA release increasingly indicate that DA release in different striatal regions is associated with different behavioral responses (Leyton et al. 2002
; Clatworthy et al., 2009
; Martinez et al., 2005
). Taken together, these data raise the possibility that there are distinct sources of individual differences in striatal DA functioning, some of which, like D2 receptor availability occur at a rather global level, while others, like DA release, have more regionally specific effects. We note, however, that a true test of dissociation of regional differences in the functional correlates of DA release will require direct tests of significant differences in correlations in the same manner as we have suggested would be needed for measures of D2-like receptor availability.
A final feature of note relates to the identification of a distinctive component loading on the DA midbrain. Midbrain DA binding primarily reflects autoreceptors, particularly of the D2-short variety (Drukarch and Stoof, 1990
; Khan et al., 1998
; Sesack et al., 1994
). The emergence of a specific component labeling this region suggests that there may be unique individual differences in autoreceptor expression that are dissociable from the more general influences on cortical and striatal DA levels. Interestingly, the amygdala-hippocampus, hypothalamus and basal forebrain also showed high positive loadings on this component. The reason for this topographically specific covariance between these regions is currently unclear. It may be speculated that this link reflects autoreceptor expression as areas such as the amygdala are known to have potent terminal D2 autoreceptors (Bull et al., 1991
), but data supporting or refuting such a hypothesis remain scarce.
F]fallypride binds at both D2 and D3 receptors, it is possible that the emergence of different components in the PCA could relate to the relative concentration of D2 vs. D3 receptors in different regions. In most cortical and subcortical regions, the D2 receptor is more abundantly expressed than the D3 receptor (Gurevich and Joyce, 1999
; MeadorWoodruff et al., 1996
), but the ratio of D2 to D3 receptor expression varies across regions. For instance, the density of D2 receptors is around six times greater than D3 densities in the dorsal caudate, but only around twice as plentiful in the basolateral amygdala and nucleus accumbens (Gurevich and Joyce, 1999
). However, the present data appears inconsistent with a distinctive D3 component. Specifically, the ventral striatum did not show a distinct pattern relative to the dorsal striatum, despite these large differences in D2/D3 receptor ratios. Similarly, the amygdala and hippocampus showed very similar patterns and a high correlation despite evidence of significant D3 receptors in the amygdala, but not the hippocampus (Murray et al., 1994
A final source of methodological influence that might impact the results relates to morphological variability across subjects. This could come in to play in two respects. First individual differences in grey matter volume or density could influence the corresponding amount of receptor sites. We have previously observed positive associations between grey matter volume and/or density in select cortical regions, and in the midbrain, thalamus and striatum (Woodward et al., 2009
). However, these are unlikely to explain the larger patterns observed in these analyses, in that cortically, the correlations between grey matter and BPND
were regional specific, whereas Component 1 of the z-transformed data occupies most of cortex. Similarly, although grey matter measures showed a correlation with BPND
in the caudate, no association was observed for the putamen, whereas, both the raw and z-transformed analyses in the present study show similarity across all striatal regions. A second manner where morphological issues might impact the results is in misregistration of regions due to the use of template brains, and partial volume averaging around the edges of structures with differing levels of D2-like receptors. We note, however, that such effects would likely produce patterns of association around the edges of structures (particularly smaller structures), but such effects were not readily apparent (the lateral thalamus is perhaps the only region where such an argument might be marshaled given the narrow band of component loadings in this region). Additionally, the large size of many of the regions with high component loadings (broad swaths of cortex, the striatum) and the correspondingly large ROIs contain enough voxels that individual differences at the edges of regions could not explain the larger pattern of associations.
To our knowledge this is the first paper to attempt to apply a voxel-wise PCA strategy to understanding the spatial organization of individual difference in neuroreceptor binding. Such a strategy may prove beneficial for a range of different receptor systems, and may capture relationships that would likely be missed using a small set of a priori ROIs. The results of such analyses have the potential to both generate novel hypotheses about the organization and cross regulation of neurotransmitter systems, and inform the design and interpretation of experiments with radioligands.