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While the dopaminergic system is important for cognitive processes, it is also sensitive to the influence of physical activity (PA). We summarize current evidence on whether PA-related changes in the human dopaminergic system are associated with alterations in cognitive performance, discuss recent advances, and highlight challenges and opportunities for future research., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Premenstrual dysphoric disorder (PMDD) is hypothesized to stem from maladaptive neural sensitivity to ovarian steroid hormone fluctuations. Recently, we found thinner cortices in individuals with PMDD, compared to healthy controls, during the symptomatic phase. Here, we aimed at investigating whether such differences illustrate state-like characteristics specific to the symptomatic phase, or trait-like features defining PMDD., Methods: Patients and controls were scanned using structural magnetic resonance imaging during the mid-follicular and late-luteal phase of the menstrual cycle. Group-by-phase interaction effects on cortical architecture metrics (cortical thickness, gyrification index, cortical complexity, and sulcal depth) were assessed using surface-based morphometry., Results: Independently of menstrual cycle phase, a main effect of diagnostic group on surface metrics was found, primarily illustrating thinner cortices (0.3 < Cohen's d > 1.1) and lower gyrification indices (0.4 < Cohen's d > 1.0) in patients compared to controls. Furthermore, menstrual cycle-specific effects were detected across all participants, depicting a decrease in cortical thickness (0.4 < Cohen's d > 1.7) and region-dependent changes in cortical folding metrics (0.4 < Cohen's d > 2.2) from the mid-follicular to the late luteal phase., Limitations: Small effects (d = 0.3) require a larger sample size to be accurately characterized., Conclusions: These findings provide initial evidence of trait-like cortical characteristics of the brain of individuals with premenstrual dysphoric disorder, together with indications of menstrual cycle-related variations in cortical architecture in patients and controls. Further investigations exploring whether these differences constitute stable vulnerability markers or develop over the years may help understand PMDD etiology., Competing Interests: Declaration of competing interest ISP has served on advisory boards or acted as invited speaker at scientific meetings for Asarina Pharma, Bayer Health Care, Gedeon Richter, Peptonics, Shire/Takeda, Sandoz, and Lundbeck A/S, on few occasions. These entities were not involved in the design, conduct or report of the present research. No conflicts of interest are declared by the other authors., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

The dopaminergic system is firmly implicated in reversal learning but human measurements of dopamine release as a correlate of reversal learning success are lacking. Dopamine release and hemodynamic brain activity in response to unexpected changes in action-outcome probabilities are here explored using simultaneous dynamic [11C]Raclopride PET-fMRI and computational modelling of behavior. When participants encounter reversed reward probabilities during a card guessing game, dopamine release is observed in associative striatum. Individual differences in absolute reward prediction error and sensitivity to errors are associated with peak dopamine receptor occupancy. The fMRI response to perseverance errors at the onset of a reversal spatially overlap with the site of dopamine release. Trial-by-trial fMRI correlates of absolute prediction errors show a response in striatum and association cortices, closely overlapping with the location of dopamine release, and separable from a valence signal in ventral striatum. The results converge to implicate striatal dopamine release in associative striatum as a central component of reversal learning, possibly signifying the need for increased cognitive control when new stimuli-responses should be learned., (© 2024. The Author(s).)

External tasks evoke characteristic fMRI BOLD signal deactivations in the default mode network (DMN). However, for the corresponding metabolic glucose demands both decreases and increases have been reported. To resolve this discrepancy, functional PET/MRI data from 50 healthy subjects performing Tetris were combined with previously published data sets of working memory, visual and motor stimulation. We show that the glucose metabolism of the posteromedial DMN is dependent on the metabolic demands of the correspondingly engaged task-positive networks. Specifically, the dorsal attention and frontoparietal network shape the glucose metabolism of the posteromedial DMN in opposing directions. While tasks that mainly require an external focus of attention lead to a consistent downregulation of both metabolism and the BOLD signal in the posteromedial DMN, cognitive control during working memory requires a metabolically expensive BOLD suppression. This indicates that two types of BOLD deactivations with different oxygen-to-glucose index may occur in this region. We further speculate that consistent downregulation of the two signals is mediated by decreased glutamate signaling, while divergence may be subject to active GABAergic inhibition. The results demonstrate that the DMN relates to cognitive processing in a flexible manner and does not always act as a cohesive task-negative network in isolation., Competing Interests: GG, SK, VP, JR, AR, LS, LC, MB, AH No competing interests declared, WW declares to having received speaker honoraria from the GE Healthcare and research grants from Ipsen Pharma, Eckert-Ziegler AG, Scintomics, and ITG; and working as a part time employee of CBmed Ltd. (Center for Biomarker Research in Medicine, Graz, Austria), MH received consulting fees and/or honoraria from Bayer Healthcare BMS, Eli Lilly, EZAG, GE Healthcare, Ipsen, ITM, Janssen, Roche, and Siemens Healthineers, RL received investigator-initiated research funding from Siemens Healthcare regarding clinical research using PET/MRI. He is a shareholder of the start-up company BM Health GmbH since 2019, (© 2023, Godbersen et al.)

Premenstrual dysphoric disorder (PMDD) is a debilitating disorder characterized by severe mood symptoms in the luteal phase of the menstrual cycle. PMDD symptoms are hypothesized to be linked to an altered sensitivity to normal luteal phase levels of allopregnanolone (ALLO), a GABA A -modulating progesterone metabolite. Moreover, the endogenous 3β-epimer of ALLO, isoallopregnanolone (ISO), has been shown to alleviate PMDD symptoms through its selective and dose-dependent antagonism of the ALLO effect. There is preliminary evidence showing altered recruitment of brain regions during emotion processing in PMDD, but whether this is associated to serum levels of ALLO, ISO or their relative concentration is unknown. In the present study, subjects with PMDD and asymptomatic controls underwent functional magnetic resonance imaging (fMRI) in the mid-follicular and the late-luteal phase of the menstrual cycle. Brain responses to emotional stimuli were investigated and related to serum levels of ovarian steroids, the neurosteroids ALLO, ISO, and their ratio ISO/ALLO. Participants with PMDD exhibited greater activity in brain regions which are part of emotion-processing networks during the late-luteal phase of the menstrual cycle. Furthermore, activity in key regions of emotion processing networks - the parahippocampal gyrus and amygdala - was differentially associated to the ratio of ISO/ALLO levels in PMDD subjects and controls. Specifically, a positive relationship between ISO/ALLO levels and brain activity was found in PMDD subjects, while the opposite was observed in controls. In conclusion, individuals with PMDD show altered emotion-induced brain responses in the late-luteal phase of the menstrual cycle which may be related to an abnormal response to physiological levels of GABA A -active neurosteroids., (© 2023. The Author(s).)

A common observation in fMRI studies using the BOLD signal is that older adults, compared with young adults, show overactivations, particularly during less demanding tasks. The neuronal underpinnings of such overactivations are not known, but a dominant view is that they are compensatory in nature and involve recruitment of additional neural resources. We scanned 23 young (20-37 years) and 34 older (65-86 years) healthy human adults of both sexes with hybrid positron emission tomography/MRI. The radioligand [18F]fluoro-deoxyglucose was used to assess dynamic changes in glucose metabolism as a marker of task-dependent synaptic activity, along with simultaneous fMRI BOLD imaging. Participants performed two verbal working memory (WM) tasks: one involving maintenance (easy) and one requiring manipulation (difficult) of information in WM. Converging activations to the WM tasks versus rest were observed for both imaging modalities and age groups in attentional, control, and sensorimotor networks. Upregulation of activity to WM-demand, comparing the more difficult to the easier task, also converged between both modalities and age groups. For regions in which older adults showed task-dependent BOLD overactivations compared with the young adults, no corresponding increases in glucose metabolism were found. To conclude, findings from the current study show that task-induced changes in the BOLD signal and synaptic activity as measured by glucose metabolism generally converge, but overactivations observed with fMRI in older adults are not coupled with increased synaptic activity, which suggests that these overactivations are not neuronal in origin. SIGNIFICANCE STATEMENT Findings of increased fMRI activations in older compared with younger adults have been suggested to reflect increased use of neuronal resources to cope with reduced brain function. The physiological underpinnings of such compensatory processes are poorly understood, however, and rest on the assumption that vascular signals accurately reflect neuronal activity. Comparing fMRI and simultaneously acquired functional positron emission tomography as an alternative index of synaptic activity, we show that age-related overactivations do not appear to be neuronal in origin. This result is important because mechanisms underlying compensatory processes in aging are potential targets for interventions aiming to prevent age-related cognitive decline., (Copyright © 2023 Stiernman et al.)

Background: Dopamine transporter (DAT) imaging is used in the diagnostic work-up in suspected parkinsonian syndromes and dementia with Lewy bodies but cannot differentiate between these syndromes, and an extra brain imaging examination of the regional cerebral blood flow (rCBF) or glucose metabolism is often needed for differential diagnosis. The requirement of two different imaging examinations is resource-consuming and inconvenient for the patients. Therefore, imaging of both cortical blood flow and DAT imaging with the same radiotracer would be more convenient and cost-effective. The aim of this study was to test whether relative regional cerebral blood flow (rCBF R ) can be measured with the DAT-specific positron emission tomography (PET) tracer [ 18 F]FE-PE2I (FE-PE2I), by validation with cerebral perfusion measured with [ 15 O]H 2 O PET (H 2 O)., Methods: The rCBF R was quantified by kinetic modeling for FE-PE2I (R1) and H 2 O (F). The R1 was calculated using the simplified reference tissue model, and F was calculated with a modified Koopman double-integration method. The linear relationship and intraclass correlation (ICC) between R1 and F were tested in image data derived from 29 patients with recent onset parkinsonism and 30 healthy controls., Results: There was a strong linear correlation across all subjects between R1 and F in the frontal, parietal, temporal, cingulate and occipital cortex as well as in the striatum (r  ≥  0.731-0.905, p  < 0.001) with a good-to-excellent ICC, ranging from 0.727 to 0.943 (p < 0.001)., Conclusions: Our results suggest that FE-PE2I may be used as a proxy for cerebral perfusion, thus potentially serving as a radiotracer for assessment of both DAT availability and rCBF R in one single dynamic scan. This could be valuable in the differential diagnosis of parkinsonian syndromes., Trial Registration: EUDRA-CT 2015-003045-26. Registered 23 October 2015 https://www.clinicaltrialsregister.eu/ctr-search/search?query=2015-003045-26., (© 2022. The Author(s).)

Premenstrual dysphoric disorder (PMDD) is a female-specific condition classified in the Diagnostic and Statical Manual-5th edition under depressive disorders. Alterations in grey matter volume, cortical thickness and folding metrics have been associated with a number of mood disorders, though little is known regarding brain morphological alterations in PMDD. Here, women with PMDD and healthy controls underwent magnetic resonance imaging (MRI) during the luteal phase of the menstrual cycle. Differences in grey matter structure between the groups were investigated by use of voxel- and surface-based morphometry. Machine learning and multivariate pattern analysis were performed to test whether MRI data could distinguish women with PMDD from healthy controls. Compared to controls, women with PMDD had smaller grey matter volume in ventral posterior cortices and the cerebellum (Cohen's d = 0.45-0.76). Region-of-interest analyses further indicated smaller volume in the right amygdala and putamen of women with PMDD (Cohen's d = 0.34-0.55). Likewise, thinner cortex was observed in women with PMDD compared to controls, particularly in the left hemisphere (Cohen's d = 0.20-0.74). Classification analyses showed that women with PMDD can be distinguished from controls based on grey matter morphology, with an accuracy up to 74%. In line with the hypothesis of an impaired top-down inhibitory circuit involving limbic structures in PMDD, the present findings point to PMDD-specific grey matter anatomy in regions of corticolimbic networks. Furthermore, the results include widespread cortical and cerebellar regions, suggesting the involvement of distinct networks in PMDD pathophysiology., (© 2022. The Author(s).)

Background: Premenstrual dysphoric disorder (PMDD) is a mood disorder characterized by psychological and physical symptoms. Differences in white matter have been associated with affective and anxiety disorders, which share some symptoms with PMDD. However, whether white matter structure differs between the brains of individuals with PMDD and healthy controls is not known, nor is its relation to symptom severity., Methods: We performed tract-based spatial statistics and voxel-based morphometry analyses of diffusion tensor imaging metrics and white matter volume, using 2 neuroimaging data sets ( n = 67 and n = 131) and a combined whole-brain and region-of-interest approach. We performed correlation analyses to investigate the relationship between regions with different white matter microstructure and volume and PMDD symptom severity., Results: We found greater fractional anisotropy in the left uncinate fasciculus ( d = 0.69) in individuals with PMDD compared to controls. Moreover, the volume of the right uncinate fasciculus was higher in individuals with PMDD compared to controls ( d = 0.40). As well, the severity of premenstrual depression was positively correlated with fractional anisotropy in the right superior longitudinal fasciculus ( r = 0.35)., Limitations: It is challenging to interpret group differences in diffusion tensor imaging metrics in terms of their underlying biophysical properties. The small size of the control group in the diffusion tensor imaging study may have prevented effects of interest from being detected., Conclusion: The findings of the present study provide evidence of differential cerebral white matter structure associated with PMDD and its symptoms., Competing Interests: Competing interests: R. Lanzenberger received support from Siemens Healthcare for clinical research using PET/MR, conference speaker honoraria and travel grants within the last 3 years from Bruker BioSpin MR and Heel, and he has been a shareholder of the start-up company BM Health GmbH since 2019. C.N. Epperson has received research grant support from Sage Therapeutics; he has served on an advisory board for Sage Therapeutics and has received honoraria and travel funding from Sage Therapeutics. I. Sundström-Poromaa was supported by a grant from the Swedish Research Council (2020-01801) and the Brain Foundation (F2020-0255), has served occasionally on advisory boards for Gedeon Richter and received honoraria as an invited speaker for Bayer Health Care, Gedeon Richter, Peptonics, Shire/Takeda, and Sandoz. E. Comasco receives funds from SciLifeLab. No other competing interests declared., (© 2022 CMA Impact Inc. or its licensors.)