An important question is to what extent
An important question is to what extent any differences in radioligand characteristics may have contributed to discrepancies between studies. Two studies on schizophrenia addressed this question directly by using [11C]SCH 23390 and [11C]NCC 112 in the same individuals, not finding any differences between the tracers with regard to group differences between patients and control subjects [72,69]. This lack of difference is in line with in vivo data showing similar contributions from 5HT2a-R, as well as lack of sensitivity to endogenous DA, as reviewed above. Another possible source of bias could be the use of different methods of quantification. For instance, some of the early studies with [11C]SCH 23390 used 2TCM-derived rate constants to estimate BPND [63,77], an approach which has shown to be unsuitable for most radioligands [109,110]. For [11C]SCH 23390 in particular, binding parameters derived using 2TCM have shown low reliability and accuracy , which may be due to the rapid Go 6983 australia of this tracer in plasma . For three studies using [11C]NCC 112, results were reported using both BPP and BPND. In the study on schizophrenia by Abi-Dargham et al. (2012), statistically significant increases in patients compared to control subjects were found only for BPP, however comparison of effect sizes between outcome measures was not possible since BPND values were not reported. Notably, BPP relies on the assumption of no differences in protein binding of the radioligand , which was trend-level different between groups. In the two remaining studies employing both BPP and BPND, both in substance use disorders, the outcome measures gave slightly different effect sizes [84,85] (Table 1). A potential explanation for these differences could be that even minor group differences in VND would cause a relatively larger impact on BPND compared to BPP, since it is included in the denominator .
Low power is a problem in neuroscience research in general, and for neuroimaging in particular, and can lead to both false negative and false positives . Since PET is an expensive method and also involves radiation exposure, an important way forward for D1-R research in psychiatric populations would be to share data . This can be done at the level of outcome measures to allow for an individual participant data meta-analysis, which makes it possible to take confounders such as age and medication into account in a more formal way . Alternatively, if raw data is shared this would also solve some of the methodological confounders by allowing for a harmonized re-analysis. Arguably, data sharing may be particularly important in research on the pathophysiology of psychiatric disorders, where disease heterogeneity is often considered to be high.
Conflicts of interest
Acknowledgements Granville J. Matheson for providing figure and help with proof reading. S.C. is supported by a grant from the Swedish Research Council (523-2014-3467).
Introduction The reticular thalamic nucleus (RTn) is a thin shell of neurons that covers the dorsal thalamus and one of the few thalamic nuclei that does not project to the cerebral cortex. Through GABAergic projections, neurons of the RTn synapse with thalamo-cortical neurons (TCs) and regulate the information output from the thalamic nuclei to different regions of the cerebral cortex (Fuentealba and Steriade, 2005, Pinault and Deschenes, 1998, Steriade, 2005). The RTn acts as an interface that selectively participates in the reciprocal exchange of information between the thalamus and the cerebral cortex (Halassa et al., 2014). It receives glutamatergic fibers mainly from cortico-thalamic neurons (CTs) and to a lesser extent from collateral TCs (Bourassa and Deschenes, 1995, Liu and Jones, 1999). RTn neurons have two firing patterns: a burst mode that occurs predominantly during deep sleep (slow wave sleep) and a tonic-firing mode predominantly linked to waking states (Pinault, 2004). The study of these different firing modes is relevant because changes in the reticular electrical activity have been associated with signs observed in schizophrenia (Ferrarelli et al., 2010, Ferrarelli and Tononi, 2011, Pratt and Morris, 2015).