Altered cortical synaptic lipid signaling leads to intermediate phenotypes of mental disorders.

Excitation/inhibition (E/I) balance plays important roles in mental disorders. Bioactive phospholipids like lysophosphatidic acid (LPA) are synthesized by the enzyme autotaxin (ATX) at cortical synapses and modulate glutamatergic transmission, and eventually alter E/I balance of cortical networks. Here, we analyzed functional consequences of altered E/I balance in 25 human subjects induced by genetic disruption of the synaptic lipid signaling modifier PRG-1, which were compared to 25 age and sex matched control subjects. Furthermore, we tested therapeutic options targeting ATX in a related mouse line. Using EEG combined with TMS in an instructed fear paradigm, neuropsychological analysis and an fMRI based episodic memory task, we found intermediate phenotypes of mental disorders in human carriers of a loss-of-function single nucleotide polymorphism of PRG-1 (PRG-1R345T/WT). Prg-1R346T/WT animals phenocopied human carriers showing increased anxiety, a depressive phenotype and lower stress resilience. Network analysis revealed that coherence and phase-amplitude coupling were altered by PRG-1 deficiency in memory related circuits in humans and mice alike. Brain oscillation phenotypes were restored by inhibtion of ATX in Prg-1 deficient mice indicating an interventional potential for mental disorders.

Putaminal dopamine modulates movement motivation in Parkinson's disease.

The relative inability to produce effortful movements is the most specific motor sign of Parkinson's disease, which is primarily characterized by loss of dopaminergic terminals in the putamen. The motor motivation hypothesis suggests that this motor deficit may not reflect a deficiency in motor control per se, but a deficiency in cost-benefit considerations for motor effort. For the first time, we investigated the quantitative effect of dopamine depletion on the motivation of motor effort in Parkinson's disease. A total of 21 early-stage, unmedicated patients with Parkinson's disease and 26 healthy controls were included. An incentivized force task was used to capture the amount of effort participants were willing to invest for different monetary incentive levels and dopamine transporter depletion in the bilateral putamen was assessed. Our results demonstrate that patients with Parkinson's disease applied significantly less grip force than healthy controls, especially for low incentive levels. Congruously, decrease of motor effort with greater loss of putaminal dopaminergic terminals was most pronounced for low incentive levels. This signifies that putaminal dopamine is most critical to motor effort when the trade-off with the benefit is poor. Taken together, we provide direct evidence that the reduction of effortful movements in Parkinson's disease depends on motivation and that this effect is associated with putaminal dopaminergic degeneration.

Dynamic properties in functional connectivity changes and striatal dopamine deficiency in Parkinson's disease.

Recent studies in Parkinson's disease (PD) patients reported disruptions in dynamic functional connectivity (dFC, i.e., a characterization of spontaneous fluctuations in functional connectivity over time). Here, we assessed whether the integrity of striatal dopamine terminals directly modulates dFC metrics in two separate PD cohorts, indexing dopamine-related changes in large-scale brain network dynamics and its implications in clinical features. We pooled data from two disease-control cohorts reflecting early PD. From the Parkinson's Progression Marker Initiative (PPMI) cohort, resting-state functional magnetic resonance imaging (rsfMRI) and dopamine transporter (DaT) single-photon emission computed tomography (SPECT) were available for 63 PD patients and 16 age- and sex-matched healthy controls. From the clinical research group 219 (KFO) cohort, rsfMRI imaging was available for 52 PD patients and 17 age- and sex-matched healthy controls. A subset of 41 PD patients and 13 healthy control subjects additionally underwent 18F-DOPA-positron emission tomography (PET) imaging. The striatal synthesis capacity of 18F-DOPA PET and dopamine terminal quantity of DaT SPECT images were extracted for the putamen and the caudate. After rsfMRI pre-processing, an independent component analysis was performed on both cohorts simultaneously. Based on the derived components, an individual sliding window approach (44 s window) and a subsequent k-means clustering were conducted separately for each cohort to derive dFC states (reemerging intra- and interindividual connectivity patterns). From these states, we derived temporal metrics, such as average dwell time per state, state attendance, and number of transitions and compared them between groups and cohorts. Further, we correlated these with the respective measures for local dopaminergic impairment and clinical severity. The cohorts did not differ regarding age and sex. Between cohorts, PD groups differed regarding disease duration, education, cognitive scores and L-dopa equivalent daily dose. In both cohorts, the dFC analysis resulted in three distinct states, varying in connectivity patterns and strength. In the PPMI cohort, PD patients showed a lower state attendance for the globally integrated (GI) state and a lower number of transitions than controls. Significantly, worse motor scores (Unified Parkinson's Disease Rating Scale Part III) and dopaminergic impairment in the putamen and the caudate were associated with low average dwell time in the GI state and a low total number of transitions. These results were not observed in the KFO cohort: No group differences in dFC measures or associations between dFC variables and dopamine synthesis capacity were observed. Notably, worse motor performance was associated with a low number of bidirectional transitions between the GI and the lesser connected (LC) state across the PD groups of both cohorts. Hence, in early PD, relative preservation of motor performance may be linked to a more dynamic engagement of an interconnected brain state. Specifically, those large-scale network dynamics seem to relate to striatal dopamine availability. Notably, most of these results were obtained only for one cohort, suggesting that dFC is impacted by certain cohort features like educational level, or disease severity. As we could not pinpoint these features with the data at hand, we suspect that other, in our case untracked, demographical features drive connectivity dynamics in PD. PRACTITIONER POINTS: Exploring dopamine's role in brain network dynamics in two Parkinson's disease (PD) cohorts, we unraveled PD-specific changes in dynamic functional connectivity. Results in the Parkinson's Progression Marker Initiative (PPMI) and the KFO cohort suggest motor performance may be linked to a more dynamic engagement and disengagement of an interconnected brain state. Results only in the PPMI cohort suggest striatal dopamine availability influences large-scale network dynamics that are relevant in motor control.

Effects of DRD2/ANKK1 and COMT Val158Met polymorphisms on stabilization against and adaptation to unexpected events.

Genetic variations affecting dopaminergic neuromodulation such as the DRD2/ANKK1 and the COMT Val158Met polymorphisms contribute to goal-directed behavior that requires a balance between stabilization and updating of current states and behaviors. Dopamine is also thought to be relevant for encoding of surprise signals to sensory input and adaptive learning. A link between goal-directed behavior and learning from surprise is therefore plausible. In the present fMRI study, we investigated whether DRD2 and COMT polymorphisms are related to behavioral responses and neural signals in the caudate nucleus and dlPFC during updating or stabilizing internal models of predictable digit sequences. To-be-detected switches between sequences and to-be-ignored digit omissions within a sequence varied by information-theoretic quantities of surprise and entropy. We found that A1 noncarriers and Val-carriers showed a lower response threshold along with increased caudate and dlPFC activation to surprising switches compared with A1-carriers and Met-homozygotes, whose dlPFC activity increased with decreasing switch surprise. In contrast, there were overall smaller differences in behavioral and neural modulation by drift surprise. Our results suggest that the impact of dopamine-relevant polymorphisms in the flexibility-stability trade-off may result in part from the role of dopamine in encoding the weight afforded to events requiring updating or stabilization.

Neural encoding of food and monetary reward delivery.

Different types of rewards such as food and money can similarly drive our behavior owing to shared brain processes encoding their subjective value. However, while the value of money is abstract and needs to be learned, the value of food is rooted in the innate processing of sensory properties and nutritional utilization. Yet, the actual consumption of food and the receipt of money have never been directly contrasted in the same experiment, questioning what unique neural processes differentiate those reward types. To fill this gap, we examined the distinct and common neural responses to the delivery of food and monetary rewards during fMRI. In a novel experimental approach, we parametrically manipulated the subjective value of food and monetary rewards by modulating the quantities of administered palatable milkshake and monetary gains. The receipt of increasing amounts of milkshake and money recruited the ventral striatum and the ventromedial prefrontal cortex, previously associated with value encoding. Notably, the consumption and the subsequent evaluation of increasing quantities of milkshake relative to money revealed an extended recruitment of brain regions related to taste, somatosensory processing, and salience. Moreover, we detected a decline of reward encoding in the ventral tegmental area, nucleus accumbens, and vmPFC, indicating that these regions may be susceptible to time-dependent effects upon accumulation of food and money rewards. Relative to monetary gains, the consumption and evaluation of palatable milkshakes engaged complex neural processing over and above value tracking, emphasizing the critical contribution of taste and other sensory properties to the processing of food rewards. Furthermore, our results highlight the need to closely monitor metabolic states and neural responses to the accumulation of rewards to pinpoint the mechanisms underlying time-dependent dynamics of reward-related processing.

Neural correlates and predictors of subjective cognitive decline in patients with Parkinson's disease.

BACKGROUND: Subjective cognitive decline (SCD) may occur very early in the course of Parkinson's disease (PD) before the onset of objective cognitive decline. Data on neural correlates and determinants of SCD in PD are rare. OBJECTIVE: The aim of the present study was to identify neural correlates as well as sociodemographic, clinical, and neuropsychological predictors of SCD in patients with PD. METHODS: We retrospectively analyzed 30 patients with PD without cognitive impairment (23% female, 66.90 ± 7.20 years, UPDRS-III: 19.83 ± 9.29), of which n = 12 patients were classified as having no SCD (control group, PD-CG) and n = 18 as having SCD (PD-SCD). Neuropsychological testing and 18-fluoro-2-deoxyglucose positron emission tomography (FDG-PET) were conducted. SCD was assessed using a questionnaire covering multiple cognitive domains. RESULTS: SCD subscores differed significantly between PD-CG and PD-SCD and correlated significantly with other scales measuring related concepts. FDG-PET whole-brain voxel-wise regression analysis revealed hypometabolism in middle frontal, middle temporal, and occipital areas, and the angular gyrus as neural correlates of SCD in PD. Next to this hypometabolism, depressive symptoms were an independent significant determinant of SCD in a stepwise regression analysis (adjusted R2 = 50.3%). CONCLUSION: This study strengthens the hypothesis of SCD being an early manifestation of future cognitive decline in PD and, more generally, early pathological changes in PD. The early identification of the vulnerability for future cognitive decline constitutes the basis for successful prevention and delay of this non-motor symptom.

Increased prefrontal top-down control in older adults predicts motor performance and age-group association.

Bimanual motor control declines during ageing, affecting the ability of older adults to maintain independence. An important underlying factor is cortical atrophy, particularly affecting frontal and parietal areas in older adults. As these regions and their interplay are highly involved in bimanual motor preparation, we investigated age-related connectivity changes between prefrontal and premotor areas of young and older adults during the preparatory phase of complex bimanual movements using high-density electroencephalography. Generative modelling showed that excitatory inter-hemispheric prefrontal to premotor coupling in older adults predicted age-group affiliation and was associated with poor motor-performance. In contrast, excitatory intra-hemispheric prefrontal to premotor coupling enabled older adults to maintain motor-performance at the cost of lower movement speed. Our results disentangle the complex interplay in the prefrontal-premotor network during movement preparation underlying reduced bimanual control and the well-known speed-accuracy trade-off seen in older adults.

Technical note: A fast and robust integrator of delay differential equations in DCM for electrophysiological data.

Dynamic causal models (DCMs) of electrophysiological data allow, in principle, for inference on hidden, bulk synaptic function in neural circuits. The directed influences between the neuronal elements of modeled circuits are subject to delays due to the finite transmission speed of axonal connections. Ordinary differential equations are therefore not adequate to capture the ensuing circuit dynamics, and delay differential equations (DDEs) are required instead. Previous work has illustrated that the integration of DDEs in DCMs benefits from sophisticated integration schemes in order to ensure rigorous parameter estimation and correct model identification. However, integration schemes that have been proposed for DCMs either emphasize speed (at the possible expense of accuracy) or robustness (but with computational costs that are problematic in practice). In this technical note, we propose an alternative integration scheme that overcomes these shortcomings and offers high computational efficiency while correctly preserving the nature of delayed effects. This integration scheme is available as open-source code in the Translational Algorithms for Psychiatry-Advancing Science (TAPAS) toolbox and can be easily integrated into existing software (SPM) for the analysis of DCMs for electrophysiological data. While this paper focuses on its application to the convolution-based formalism of DCMs, the new integration scheme can be equally applied to more advanced formulations of DCMs (e.g. conductance based models). Our method provides a new option for electrophysiological DCMs that offers the speed required for scientific projects, but also the accuracy required for rigorous translational applications, e.g. in computational psychiatry.

Technical Note: Modulation of fMRI brainstem responses by transcutaneous vagus nerve stimulation.

Our increasing knowledge about gut-brain interaction is revolutionising the understanding of the links between digestion, mood, health, and even decision making in our everyday lives. In support of this interaction, the vagus nerve is a crucial pathway transmitting diverse gut-derived signals to the brain to monitor of metabolic status, digestive processes, or immune control to adapt behavioural and autonomic responses. Hence, neuromodulation methods targeting the vagus nerve are currently explored as a treatment option in a number of clinical disorders, including diabetes, chronic pain, and depression. The non-invasive variant of vagus nerve stimulation (VNS), transcutaneous auricular VNS (taVNS), has been implicated in both acute and long-lasting effects by modulating afferent vagus nerve target areas in the brain. The physiology of neither of those effects is, however, well understood, and evidence for neuronal response upon taVNS in vagal afferent projection regions in the brainstem and its downstream targets remain to be established. Therefore, to examine time-dependent effects of taVNS on brainstem neuronal responses in healthy human subjects, we applied taVNS during task-free fMRI in a single-blinded crossover design. During fMRI data acquisition, we either stimulated the left earlobe (sham), or the target zone of the auricular branch of the vagus nerve in the outer ear (cymba conchae, verum) for several minutes, both followed by a short 'stimulation OFF' period. Time-dependent effects were assessed by averaging the BOLD response for consecutive 1-minute periods in an ROI-based analysis of the brainstem. We found a significant response to acute taVNS stimulation, relative to the control condition, in downstream targets of vagal afferents, including the nucleus of the solitary tract, the substantia nigra, and the subthalamic nucleus. Most of these brainstem regions remarkably showed increased activity in response to taVNS, and these effect sustained during the post-stimulation period. These data demonstrate that taVNS activates key brainstem regions, and highlight the potential of this approach to modulate vagal afferent signalling. Furthermore, we show that carry-over effects need to be considered when interpreting fMRI data in the context of general vagal neurophysiology and its modulation by taVNS.

Model-based prediction of muscarinic receptor function from auditory mismatch negativity responses.

Drugs affecting neuromodulation, for example by dopamine or acetylcholine, take centre stage among therapeutic strategies in psychiatry. These neuromodulators can change both neuronal gain and synaptic plasticity and therefore affect electrophysiological measures. An important goal for clinical diagnostics is to exploit this effect in the reverse direction, i.e., to infer the status of specific neuromodulatory systems from electrophysiological measures. In this study, we provide proof-of-concept that the functional status of cholinergic (specifically muscarinic) receptors can be inferred from electrophysiological data using generative (dynamic causal) models. To this end, we used epidural EEG recordings over two auditory cortical regions during a mismatch negativity (MMN) paradigm in rats. All animals were treated, across sessions, with muscarinic receptor agonists and antagonists at different doses. Together with a placebo condition, this resulted in five levels of muscarinic receptor status. Using a dynamic causal model - embodying a small network of coupled cortical microcircuits - we estimated synaptic parameters and their change across pharmacological conditions. The ensuing parameter estimates associated with (the neuromodulation of) synaptic efficacy showed both graded muscarinic effects and predictive validity between agonistic and antagonistic pharmacological conditions. This finding illustrates the potential utility of generative models of electrophysiological data as computational assays of muscarinic function. In application to EEG data of patients from heterogeneous spectrum diseases, e.g. schizophrenia, such models might help identify subgroups of patients that respond differentially to cholinergic treatments. SIGNIFICANCE STATEMENT: In psychiatry, the vast majority of pharmacological treatments affect actions of neuromodulatory transmitters, e.g. dopamine or acetylcholine. As treatment is largely trial-and-error based, one of the goals for computational psychiatry is to construct mathematical models that can serve as "computational assays" and infer the status of specific neuromodulatory systems in individual patients. This translational neuromodeling strategy has great promise for electrophysiological data in particular but requires careful validation. The present study demonstrates that the functional status of cholinergic (muscarinic) receptors can be inferred from electrophysiological data using dynamic causal models of neural circuits. While accuracy needs to be enhanced and our results must be replicated in larger samples, our current results provide proof-of-concept for computational assays of muscarinic function using EEG.

The default mode network and cognition in Parkinson's disease: A multimodal resting-state network approach.

Involvement of the default mode network (DMN) in cognitive symptoms of Parkinson's disease (PD) has been reported by resting-state functional MRI (rsfMRI) studies. However, the relation to metabolic measures obtained by [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) is largely unknown. We applied multimodal resting-state network analysis to clarify the association between intrinsic metabolic and functional connectivity abnormalities within the DMN and their significance for cognitive symptoms in PD. PD patients were classified into normal cognition (n = 36) and mild cognitive impairment (MCI; n = 12). The DMN was identified by applying an independent component analysis to FDG-PET and rsfMRI data of a matched subset (16 controls and 16 PD patients) of the total cohort. Besides metabolic activity, metabolic and functional connectivity within the DMN were compared between the patients' groups and healthy controls (n = 16). Glucose metabolism was significantly reduced in all DMN nodes in both patient groups compared to controls, with the lowest uptake in PD-MCI (p < .05). Increased metabolic and functional connectivity along fronto-parietal connections was identified in PD-MCI patients compared to controls and unimpaired patients. Functional connectivity negatively correlated with cognitive composite z-scores in patients (r = -.43, p = .005). The current study clarifies the commonalities of metabolic and hemodynamic measures of brain network activity and their individual significance for cognitive symptoms in PD, highlighting the added value of multimodal resting-state network approaches for identifying prospective biomarkers.

The structural connectivity of subthalamic deep brain stimulation correlates with impulsivity in Parkinson's disease.

Subthalamic deep brain stimulation (STN-DBS) for Parkinson's disease treats motor symptoms and improves quality of life, but can be complicated by adverse neuropsychiatric side-effects, including impulsivity. Several clinically important questions remain unclear: can 'at-risk' patients be identified prior to DBS; do neuropsychiatric symptoms relate to the distribution of the stimulation field; and which brain networks are responsible for the evolution of these symptoms? Using a comprehensive neuropsychiatric battery and a virtual casino to assess impulsive behaviour in a naturalistic fashion, 55 patients with Parkinson's disease (19 females, mean age 62, mean Hoehn and Yahr stage 2.6) were assessed prior to STN-DBS and 3 months postoperatively. Reward evaluation and response inhibition networks were reconstructed with probabilistic tractography using the participant-specific subthalamic volume of activated tissue as a seed. We found that greater connectivity of the stimulation site with these frontostriatal networks was related to greater postoperative impulsiveness and disinhibition as assessed by the neuropsychiatric instruments. Larger bet sizes in the virtual casino postoperatively were associated with greater connectivity of the stimulation site with right and left orbitofrontal cortex, right ventromedial prefrontal cortex and left ventral striatum. For all assessments, the baseline connectivity of reward evaluation and response inhibition networks prior to STN-DBS was not associated with postoperative impulsivity; rather, these relationships were only observed when the stimulation field was incorporated. This suggests that the site and distribution of stimulation is a more important determinant of postoperative neuropsychiatric outcomes than preoperative brain structure and that stimulation acts to mediate impulsivity through differential recruitment of frontostriatal networks. Notably, a distinction could be made amongst participants with clinically-significant, harmful changes in mood and behaviour attributable to DBS, based upon an analysis of connectivity and its relationship with gambling behaviour. Additional analyses suggested that this distinction may be mediated by the differential involvement of fibres connecting ventromedial subthalamic nucleus and orbitofrontal cortex. These findings identify a mechanistic substrate of neuropsychiatric impairment after STN-DBS and suggest that tractography could be used to predict the incidence of adverse neuropsychiatric effects. Clinically, these results highlight the importance of accurate electrode placement and careful stimulation titration in the prevention of neuropsychiatric side-effects after STN-DBS.

Network degeneration in Parkinson's disease: multimodal imaging of nigro-striato-cortical dysfunction.

The spreading hypothesis of neurodegeneration assumes an expansion of neural pathologies along existing neural pathways. Multimodal neuroimaging studies have demonstrated distinct topographic patterns of cerebral pathologies in neurodegeneration. For Parkinson's disease the hypothesis so far rests largely on histopathological evidence of α-synuclein spreading in a characteristic pattern and progressive nigrostriatal dopamine depletion. Functional consequences of nigrostriatal dysfunction on cortical activity remain to be elucidated. Our goal was to investigate multimodal imaging correlates of degenerative processes in Parkinson's disease by assessing dopamine depletion and its potential effect on striatocortical connectivity networks and cortical metabolism in relation to parkinsonian symptoms. We combined 18F-DOPA-PET, 18F-fluorodeoxyglucose (FDG)-PET and resting state functional MRI to multimodally characterize network alterations in Parkinson's disease. Forty-two patients with mild-to-moderate stage Parkinson's disease and 14 age-matched healthy control subjects underwent a multimodal imaging protocol and comprehensive clinical examination. A voxel-wise group comparison of 18F-DOPA uptake identified the exact location and extent of putaminal dopamine depletion in patients. Resulting clusters were defined as seeds for a seed-to-voxel functional connectivity analysis. 18F-FDG metabolism was compared between groups at a whole-brain level and uptake values were extracted from regions with reduced putaminal connectivity. To unravel associations between dopaminergic activity, striatocortical connectivity, glucose metabolism and symptom severity, correlations between normalized uptake values, seed-to-cluster ß-values and clinical parameters were tested while controlling for age and dopaminergic medication. Aside from cortical hypometabolism, 18F-FDG-PET data for the first time revealed a hypometabolic midbrain cluster in patients with Parkinson's disease that comprised caudal parts of the bilateral substantia nigra pars compacta. Putaminal dopamine synthesis capacity was significantly reduced in the bilateral posterior putamen and correlated with ipsilateral nigral 18F-FDG uptake. Resting state functional MRI data indicated significantly reduced functional connectivity between the dopamine depleted putaminal seed and cortical areas primarily belonging to the sensorimotor network in patients with Parkinson's disease. In the inferior parietal cortex, hypoconnectivity in patients was significantly correlated with lower metabolism (left P = 0.021, right P = 0.018). Of note, unilateral network alterations quantified with different modalities corresponded with contralateral motor impairments. In conclusion, our results support the hypothesis that degeneration of nigrostriatal fibres functionally impairs distinct striatocortical connections, disturbing the efficient interplay between motor processing areas and impairing motor control in patients with Parkinson's disease. The present study is the first to reveal trimodal evidence for network-dependent degeneration in Parkinson's disease by outlining the impact of functional nigrostriatal pathway impairment on striatocortical functional connectivity networks and cortical metabolism.

GBA Variants in Parkinson's Disease: Clinical, Metabolomic, and Multimodal Neuroimaging Phenotypes.

BACKGROUND: Alterations in the GBA gene (NM_000157.3) are the most important genetic risk factor for Parkinson's disease (PD). Biallelic GBA mutations cause the lysosomal storage disorder Gaucher's disease. The GBA variants p.E365K and p.T408M are associated with PD but not with Gaucher's disease. The pathophysiological role of these variants needs to be further explored. OBJECTIVE: This study analyzed clinical, neuropsychological, metabolic, and neuroimaging phenotypes of patients with PD carrying the GBA variants p.E365K and p.T408M. METHODS: GBA was sequenced in 56 patients with mid-stage PD. Carriers of GBA variants were compared with noncarriers regarding clinical history and symptoms, neuropsychological features, metabolomics, and multimodal neuroimaging. Blood plasma gas chromatography coupled to mass spectrometry, 6-[18 F]fluoro-L-Dopa positron emission tomography (PET), [18 F]fluorodeoxyglucose PET, and resting-state functional magnetic resonance imaging were performed. RESULTS: Sequence analysis detected 13 heterozygous GBA variant carriers (7 with p.E365K, 6 with p.T408M). One patient carried a GBA mutation (p.N409S) and was excluded. Clinical history and symptoms were not significantly different between groups. Global cognitive performance was lower in variant carriers. Metabolomic group differences were suggestive of more severe PD-related alterations in carriers versus noncarriers. Both PET scans showed signs of a more advanced disease; [18 F]fluorodeoxyglucose PET and functional magnetic resonance imaging showed similarities with Lewy body dementia and PD dementia in carriers. CONCLUSIONS: This is the first study to comprehensively assess (neuro-)biological phenotypes of GBA variants in PD. Metabolomics and neuroimaging detected more significant group differences than clinical and behavioral evaluation. These alterations could be promising to monitor effects of disease-modifying treatments targeting glucocerebrosidase metabolism. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The structural connectivity of discrete networks underlies impulsivity and gambling in Parkinson's disease.

Impulsivity in Parkinson's disease may be mediated by faulty evaluation of rewards or the failure to inhibit inappropriate choices. Despite prior work suggesting that distinct neural networks underlie these cognitive operations, there has been little study of these networks in Parkinson's disease, and their relationship to inter-individual differences in impulsivity. High-resolution diffusion MRI data were acquired from 57 individuals with Parkinson's disease (19 females, mean age 62, mean Hoehn and Yahr stage 2.6) prior to surgery for deep brain stimulation. Reward evaluation and response inhibition networks were reconstructed with seed-based probabilistic tractography. Impulsivity was evaluated using two approaches: (i) neuropsychiatric instruments were used to assess latent constructs of impulsivity, including trait impulsiveness and compulsivity, disinhibition, and also impatience; and (ii) participants gambled in an ecologically-valid virtual casino to obtain a behavioural read-out of explorative, risk-taking, impulsive behaviour. Multivariate analyses revealed that different components of impulsivity were associated with distinct variations in structural connectivity, implicating both reward evaluation and response inhibition networks. Larger bet sizes in the virtual casino were associated with greater connectivity of the reward evaluation network, particularly bilateral fibre tracts between the ventral striatum and ventromedial prefrontal cortex. In contrast, weaker connectivity of the response inhibition network was associated with increased exploration of alternative slot machines in the virtual casino, with right-hemispheric tracts between the subthalamic nucleus and the pre-supplementary motor area contributing most strongly. Further, reduced connectivity of the reward evaluation network was associated with more 'double or nothing' gambles, weighted by connections between the subthalamic nucleus and ventromedial prefrontal cortex. Notably, the variance explained by structural connectivity was higher for behavioural indices of impulsivity, derived from clinician-administered tasks and the gambling paradigm, as compared to questionnaire data. Lastly, a clinically-meaningful distinction could be made amongst participants with a history of impulse control behaviours based on the interaction of their network connectivity with medication dosage and gambling behaviour. In summary, we report structural brain-behaviour covariation in Parkinson's disease with distinct reward evaluation and response inhibition networks that underlie dissociable aspects of impulsivity (cf. choosing and stopping). More broadly, our findings demonstrate the potential of using naturalistic paradigms and neuroimaging techniques in clinical settings to assist in the identification of those susceptible to harmful behaviours.

Dopamine metabolism of the nucleus accumbens and fronto-striatal connectivity modulate impulse control.

Impulsive-compulsive behaviours like pathological gambling or hypersexuality are a frequent side effect of dopamine replacement therapy in patients with Parkinson's disease. Multiple imaging studies suggest a significant reduction of presynaptic dopamine transporters in the nucleus accumbens to be a predisposing factor, reflecting either a reduction of mesolimbic projections or, alternatively, a lower presynaptic dopamine transporter expression per se. Here, we aimed to test the hypothesis of fewer mesolimbic projections as a risk factor by using dopamine synthesis capacity as a proxy of dopaminergic terminal density. Furthermore, previous studies have demonstrated a reduction of fronto-striatal connectivity to be associated with increased risk of impulsive-compulsive behaviour in Parkinson's disease. Therefore, another aim of this study was to investigate the relationship between severity of impulsive-compulsive behaviour, dopamine synthesis capacity and fronto-striatal connectivity. Eighty participants underwent resting state functional MRI and anatomical T1-weighted images [mean age: 68 ± 9.9 years, 67% male (patients)]. In 59 participants, 18F-DOPA-PET was obtained and voxel-wise Patlak slopes indicating dopamine synthesis capacity were calculated. All participants completed the QUIP-RS questionnaire, a well validated test to quantify severity of impulsive-compulsive behaviour in Parkinson's disease. A voxel-wise correlation analysis between dopamine synthesis capacity and QUIP-RS score was calculated for striatal regions. To investigate the relationship between symptom severity and functional connectivity, voxel-wise correlations were performed. A negative correlation was found between dopamine synthesis capacity and QUIP-RS score in the nucleus accumbens (r = -0.57, P = 0.001), a region functionally connected to the rostral anterior cingulate cortex. The connectivity strength was modulated by QUIP-RS, i.e. patients with more severe impulsive-compulsive behaviours had a weaker functional connectivity between rostral anterior cingulate cortex and the nucleus accumbens. In addition, cortical thickness and severity of impulsive-compulsive behaviour were positively correlated in the subgenual rostral anterior cingulate cortex. We found three factors to be associated with severity of impulsive-compulsive behaviour: (i) decreased dopamine synthesis capacity in the nucleus accumbens; (ii) decreased functional connectivity of the rostral anterior cingulate cortex with the nucleus accumbens; and (iii) increased cortical thickness of the subgenual rostral anterior cingulate cortex. Rather than a downregulation of dopamine transporters, a reduction of mesolimbic dopaminergic projections in conjunction with a dysfunctional rostral anterior cingulate cortex-a region known to play a key role in impulse control-could be the most crucial neurobiological risk factor for the development of impulsive-compulsive behaviours in patients with Parkinson's disease under dopamine replacement therapy.

Influence of vmPFC on dmPFC Predicts Valence-Guided Belief Formation.

When updating beliefs about their future prospects, people tend to disregard bad news. By combining fMRI with computational and dynamic causal modeling, we identified neurocircuitry mechanisms underlying this optimism bias to test for valence-guided belief formation. In each trial of the fMRI task, participants (n = 24, 10 male) estimated the base rate (eBR) and their risks of experiencing negative future events, were confronted with the actual BR, and finally had the opportunity to update their initial self-related risk estimate. We demonstrated an optimism bias by revealing greater belief updates in response to good over bad news (i.e., learning that the actual BR is lower or higher than expected) while controlling for confounds (estimation error and personal relevance of the new information). Updating was favorable when the final belief about risks improved (or at least did not worsen) relative to the initial risk estimate. This valence of updating was encoded by the ventromedial prefrontal cortex (vmPFC) associated with the valuation of rewards. Within the updating circuit, the vmPFC filtered the incoming signal in a valence-dependent manner and influenced the dorsomedial prefrontal cortex (dmPFC). Both the valence-encoding activity in the vmPFC and its influence on the dmPFC predicted individual magnitudes of the optimism bias. Our results indicate that updating was biased by the motivation to maximize desirable beliefs, mediated by the influence of the valuation system on further cognitive processing. Therefore, although it provides the very basis for human reasoning, belief formation is essentially distorted to promote desired conclusions.SIGNIFICANCE STATEMENT The question of whether human reasoning is biased by desires and goals is crucial for everyday social, professional, and economic decisions. How much our belief formation is influenced by what we want to believe is, however, still debated. Our study confirms that belief updates are indeed optimistically biased. Critically, the bias depends on the recruitment of the brain valuation system and the influence of this system on neural regions involved in reasoning. These neurocircuit interactions support the notion that the motivation to maximize pleasant beliefs reinforces those cognitive processes that are most likely to yield the desired conclusion.

Modulation of midbrain neurocircuitry by intranasal insulin.

Insulin modulates dopamine neuron activity in midbrain and affects processes underlying food intake behaviour, including impulsivity and reward processing. Here, we used intranasal administration and task-free functional MRI in humans to assess time- and dose-dependent effects of insulin on functional connectivity of the dopaminergic midbrain - and how these effects varied depending on systemic insulin sensitivity as measured by HOMA-IR. Specifically, we used a repeated-measures design with factors dose (placebo, 40 IU, 100 IU, 160 IU), time (7 time points during a 90 min post-intervention interval), and group (low vs. high HOMA-IR). A factorial analysis identified a three-way interaction (with whole-brain significance) with regard to functional connectivity between midbrain and the ventromedial prefrontal cortex. This interaction demonstrates that systemic insulin sensitivity modulates the temporal course and dose-dependent effects of intranasal insulin on midbrain functional connectivity. It suggests that altered insulin sensitivity may impact on dopaminergic projections of the midbrain and might underlie the dysregulation of reward-related and motivational behaviour in obesity and diabetes. Perhaps most importantly, the time courses of midbrain functional connectivity we present may provide useful guidance for the design of future human studies that utilize intranasal insulin administration.

Dopamine substitution alters effective connectivity of cortical prefrontal, premotor, and motor regions during complex bimanual finger movements in Parkinson's disease.

Bimanual coordination is impaired in Parkinson's disease (PD), affecting patients' quality of life. Besides dysfunction of the basal ganglia network, alterations of cortical oscillatory coupling, particularly between prefrontal and (pre-)motoric areas, are thought to underlie this impairment. Here, we studied 16 PD patients OFF and ON medication and age-matched healthy controls recording high-resolution electroencephalography (EEG) during performance of spatially coupled and uncoupled bimanual finger movements. Dynamic causal modeling (DCM) for induced responses was used to infer task-induced effective connectivity within a network comprising bilateral prefrontal cortex (PFC), lateral premotor cortex (lPM), supplementary motor area (SMA), and primary motor cortex (M1). Performing spatially coupled movements, excitatory left-hemispheric PFC to lPM coupling was significantly stronger in controls compared to unmedicated PD patients. Levodopa-induced enhancement of this connection correlated with increased movement accuracy. During performance of spatially uncoupled movements, PD patients OFF medication exhibited inhibitory connectivity from left PFC to SMA. Levodopa intake diminished these inhibitory influences and restored excitatory PFC to lPM coupling. This restoration, however, did not improve motor function. Concluding, our results indicate that lateralization of prefrontal to premotor connectivity in PD can be augmented by levodopa substitution and is of compensatory nature up to a certain extent of complexity.

Integrative analysis of blood metabolomics and PET brain neuroimaging data for Parkinson's disease.

BACKGROUND: The diagnosis of Parkinson's disease (PD) often remains a clinical challenge. Molecular neuroimaging can facilitate the diagnostic process. The diagnostic potential of metabolomic signatures has recently been recognized. METHODS: We investigated whether the joint data analysis of blood metabolomics and PET imaging by machine learning provides enhanced diagnostic discrimination and gives further pathophysiological insights. Blood plasma samples were collected from 60 PD patients and 15 age- and gender-matched healthy controls. We determined metabolomic profiles by gas chromatography coupled to mass spectrometry (GC-MS). In the same cohort and at the same time we performed FDOPA PET in 44 patients and 14 controls and FDG PET in 51 patients and 16 controls. 18 PD patients were available for a follow-up exam after one year. Both data sets were analysed by two machine learning approaches, applying either linear support vector machines or random forests within a leave-one-out cross-validation scheme and computing receiver operating characteristic (ROC) curves. RESULTS: In the metabolomics data, the baseline comparison between cases and controls as well as the follow-up assessment of patients pointed to metabolite changes associated with oxidative stress and inflammation. For the FDOPA and FDG PET data, the diagnostic predictive performance (DPP) in the ROC analyses was highest when combining imaging features with metabolomics data (ROC AUC for best FDOPA + metabolomics model: 0.98; AUC for best FDG + metabolomics model: 0.91). DPP was lower when using only PET attributes or only metabolomics signatures. CONCLUSION: Integrating blood metabolomics data combined with PET data considerably enhances the diagnostic discrimination power. Metabolomic signatures also indicate interesting disease-inherent changes in cellular processes, including oxidative stress response and inflammation.