Resting-state alterations in behavioral variant frontotemporal dementia are related to the distribution of monoamine and GABA neurotransmitter systems.

Background: Aside to clinical changes, behavioral variant frontotemporal dementia (bvFTD) is characterized by progressive structural and functional alterations in frontal and temporal regions. We examined if there is a selective vulnerability of specific neurotransmitter systems in bvFTD by evaluating the link between disease-related functional alterations and the spatial distribution of specific neurotransmitter systems and their underlying gene expression levels. Methods: Maps of fractional amplitude of low-frequency fluctuations (fALFF) were derived as a measure of local activity from resting-state functional magnetic resonance imaging for 52 bvFTD patients (mean age = 61.5 ± 10.0 years; 14 females) and 22 healthy controls (HC) (mean age = 63.6 ± 11.9 years; 13 females). We tested if alterations of fALFF in patients co-localize with the non-pathological distribution of specific neurotransmitter systems and their coding mRNA gene expression. Furthermore, we evaluated if the strength of co-localization is associated with the observed clinical symptoms. Results: Patients displayed significantly reduced fALFF in frontotemporal and frontoparietal regions. These alterations co-localized with the distribution of serotonin (5-HT1b and 5-HT2a) and γ-aminobutyric acid type A (GABAa) receptors, the norepinephrine transporter (NET), and their encoding mRNA gene expression. The strength of co-localization with NET was associated with cognitive symptoms and disease severity of bvFTD. Conclusions: Local brain functional activity reductions in bvFTD followed the distribution of specific neurotransmitter systems indicating a selective vulnerability. These findings provide novel insight into the disease mechanisms underlying functional alterations. Our data-driven method opens the road to generate new hypotheses for pharmacological interventions in neurodegenerative diseases even beyond bvFTD. Funding: This study has been supported by the German Consortium for Frontotemporal Lobar Degeneration, funded by the German Federal Ministry of Education and Research (BMBF; grant no. FKZ01GI1007A).

Metreleptin Robustly Increases Resting-state Brain Connectivity in Treatment-naïve Female Patients With Lipodystrophy.

Context: Research in lipodystrophy (LD) and its treatment with metreleptin has not only helped patients with LD but has opened new directions in investigating leptin's role in metabolism and the regulation of eating behavior. Previously, in a study with patients with LD undergoing metreleptin treatment using functional magnetic resonance imaging (MRI), we found significantly increased resting-state brain connectivity in 3 brain areas including the hypothalamus. Objective: In this study, we aimed to reproduce our functional MRI findings in an independent sample and compare results to healthy participants. Design: Measurements in 4 female patients with LD undergoing metreleptin treatment and 3 healthy untreated controls were performed at 4 different time points over 12 weeks. To identify treatment-related brain connectivity alterations, eigenvector centrality was computed from resting-state functional MRI data for each patient and each session. Thereafter, analysis aimed at detecting consistent brain connectivity changes over time across all patients. Results: In parallel to metreleptin treatment of the patients with LD, we found a significant brain connectivity increase in the hypothalamus and bilaterally in posterior cingulate gyrus. Using a 3-factorial model, a significant interaction between group and time was found in the hypothalamus. Conclusions: Investigating brain connectivity alterations with metreleptin treatment using an independent sample of patients with LD, we have reproduced an increase of brain connectivity in hedonic and homeostatic central nervous networks observed previously with metreleptin treatment. These results are an important contribution to ascertain brain leptin action and help build a foundation for further research of central nervous effects of this important metabolic hormone.

Reward Processing During Monetary Incentive Delay Task After Leptin Substitution in Lipodystrophy-an fMRI Case Series.

Context: Behaviorally, the most pronounced effects of leptin substitution in leptin deficiency are the hunger-decreasing and postprandial satiety-prolonging effects of the adipokine. Previously, with functional magnetic resonance imaging (MRI), we and others showed that eating behavior-controlling effects are at least in part conveyed by the reward system. However, to date, it is unclear if leptin only modulates eating behavior specific brain reward action or if it also alters the reward function of the brain unrelated to eating behavior. Objective: We investigated with functional MRI the effects of metreleptin on the reward system in a reward task unrelated to eating behavior, the monetary incentive delay task. Design: Measurements in 4 patients with the very rare disease of lipodystrophy (LD), resulting in leptin deficiency, and 3 untreated healthy control persons were performed at 4 different time points: before start and over 12 weeks of metreleptin treatment. Inside the MRI scanner, participants performed the monetary incentive delay task and brain activity during the reward receipt phase of the trial was analyzed. Results: We found a reward-related brain activity decrease in our 4 patients with LD over the 12 weeks of metreleptin treatment in the subgenual region, a brain area associated with the reward network, which was not observed in our 3 untreated healthy control persons. Conclusions: These results suggest that leptin replacement in LD induces changes of brain activity during reward reception processing completely unrelated to eating behavior or food stimuli. This could suggest eating behavior-unrelated functions of leptin in the human reward system. Trial registration: The trial is registered as trial No. 147/10-ek at the ethics committee of the University of Leipzig and at the State Directorate of Saxony (Landesdirektion Sachsen).

Brain dysconnectivity with heart failure.

Structural brain damage associated with heart failure is well described; however, little is known about associated changes in various specific brain functions that bear immediate clinical relevance. A satisfactory pathophysiological link between heart failure and decline in cognitive function is still missing. In the present study, we aim to detect functional correlates of heart failure in terms of alterations in functional brain connectivity (quantified by functional magnetic resonance imaging) related to cognitive performance assessed by neuropsychological testing. Eighty patients were post hoc grouped into subjects with and without coronary artery disease. The coronary artery disease patients were further grouped as presenting with or without heart failure according to the guidelines of the European Society of Cardiology. On the basis of resting-state functional magnetic resonance imaging, brain connectivity was investigated using network centrality as well as seed-based correlation. Statistical analysis aimed at specifying centrality group differences and potential correlations between centrality and heart failure-related measures including left ventricular ejection fraction and serum concentrations of N-terminal fragment of the pro-hormone brain-type natriuretic peptide. The resulting correlation maps were then analysed using a flexible factorial model with the factors 'heart failure' and 'cognitive performance'. Our core findings are: (i) A statistically significant network centrality decrease was found to be associated with heart failure primarily in the precuneus, i.e. we show a positive correlation between centrality and left ventricular ejection fraction as well as a negative correlation between centrality and N-terminal fragment of the pro-hormone brain-type natriuretic peptide. (ii) Seed-based correlation analysis showed a significant interaction between heart failure and cognitive performance related to a significant decrease of precuneus connectivity to other brain regions. We obtained these results by different analysis approaches indicating the robustness of the findings we report here. Our results suggest that the precuneus is a brain region involved in connectivity decline in patients with heart failure, possibly primarily or already at an early stage. Current models of Alzheimer's disease-having pathophysiological risk factors in common with cerebrovascular disorders-also consider reduced precuneus connectivity as a marker of brain degeneration. Consequently, we propose that heart failure and Alzheimer's disease exhibit partly overlapping pathophysiological paths or have common endpoints associated with a more or less severe decrease in brain connectivity. This is further supported by specific functional connectivity alterations between the precuneus and widely distributed cortical regions, particularly in patients showing reduced cognitive performance.

Improving fMRI in Parkinson's disease by accounting for brain region-specific activity patterns.

In functional magnetic imaging (fMRI) in Parkinson's disease (PD), a paradigm consisting of blocks of finger tapping and rest along with a corresponding general linear model (GLM) is often used to assess motor activity. However, this method has three limitations: (i) Due to the strong magnetic field and the confined environment of the cylindrical bore, it is troublesome to accurately monitor motor output and, therefore, variability in the performed movement is typically ignored. (ii) Given the loss of dopaminergic neurons and ongoing compensatory brain mechanisms, motor control is abnormal in PD. Therefore, modeling of patients' tapping with a constant amplitude (using a boxcar function) and the expected Parkinsonian motor output are prone to mismatch. (iii) The motor loop involves structures with distinct hemodynamic responses, for which only one type of modeling (e.g., modeling the whole block of finger tapping) may not suffice to capture these structure's temporal activation. The first two limitations call for considering results from online recordings of the real motor output that may lead to significant sensitivity improvements. This was shown in previous work using a non-magnetic glove to capture details of the patients' finger movements in a so-called kinematic approach. For the third limitation, modeling motion initiation instead of the whole tapping block has been suggested to account for different temporal activation signatures of the motor loop's structures. In the present study we propose improvements to the GLM as a tool to study motor disorders. For this, we test the robustness of the kinematic approach in an expanded cohort (n = 31), apply more conservative statistics than in previous work, and evaluate the benefits of an event-related model function. Our findings suggest that the integration of the kinematic approach offers a general improvement in detecting activations in subcortical structures, such as the basal ganglia. Additionally, modeling motion initiation using an event-related design yielded superior performance in capturing medication-related effects in the putamen. Our results may guide adaptations in analysis strategies for functional motor studies related to PD and also in more general applications.

Structural correlates of language processing in primary progressive aphasia.

Understanding the relationships between brain structure and language behaviour in primary progressive aphasia provides crucial information about these diseases' pathomechanisms. However, previous investigations have been limited from providing a statistically reliable view of broad language abilities by sample size, variant focus and task focus. In this study, the authors aimed to determine the relationship between brain structure and language behaviour in primary progressive aphasia, to determine the degree to which task-associated regions were atrophied across disease variants and to determine the degree to which task-related atrophy overlaps across disease variants. Participants were 118 primary progressive aphasia patients and 61 healthy, age-matched controls tested from 2011 to 2018 in the German Consortium for Frontotemporal Lobar Degeneration cohort. Diagnosis of primary progressive aphasia required progressive deterioration of mainly speech and language for ≥ 2 years, and variant was diagnosed by the criteria of Gorno-Tempini et al. (Classification of primary progressive aphasia and its variants. Neurology. 2011;76(11):1006-1014). Twenty-one participants not fulfilling a specific subtype were classified as mixed-variant and excluded. Language tasks of interest included the Boston naming test, a German adaptation of the Repeat and Point task, phonemic and category fluency tasks and the reading/writing subtest of the Aachen Aphasia Test. Brain structure was measured by cortical thickness. We observed networks of language task-associated temporal, frontal and parietal cortex. Overlapping task-associated atrophy was observed in the left lateral, ventral and medial temporal lobes, middle and superior frontal gyri, supramarginal gyrus and insula. Some regions, primarily in the perisylvian region, were associated with language behaviour despite showing no significant atrophy. The results crucially extend less powerful studies associating brain and language measures in primary progressive aphasia. Cross-variant atrophy in task-associated regions suggests partially shared underlying deficits, whereas unique atrophy reinforces variant-specific deficits. Language task-related regions that are not obviously atrophied suggest regions of future network disruption and encourage understanding of task deficits beyond clearly atrophied cortex. These results may pave the way for new treatment approaches.

Multiclass prediction of different dementia syndromes based on multi-centric volumetric MRI imaging.

INTRODUCTION: Dementia syndromes can be difficult to diagnose. We aimed at building a classifier for multiple dementia syndromes using magnetic resonance imaging (MRI). METHODS: Atlas-based volumetry was performed on T1-weighted MRI data of 426 patients and 51 controls from the multi-centric German Research Consortium of Frontotemporal Lobar Degeneration including patients with behavioral variant frontotemporal dementia, Alzheimer's disease, the three subtypes of primary progressive aphasia, i.e., semantic, logopenic and nonfluent-agrammatic variant, and the atypical parkinsonian syndromes progressive supranuclear palsy and corticobasal syndrome. Support vector machine classification was used to classify each patient group against controls (binary classification) and all seven diagnostic groups against each other in a multi-syndrome classifier (multiclass classification). RESULTS: The binary classification models reached high prediction accuracies between 71 and 95% with a chance level of 50%. Feature importance reflected disease-specific atrophy patterns. The multi-syndrome model reached accuracies of more than three times higher than chance level but was far from 100%. Multi-syndrome model performance was not homogenous across dementia syndromes, with better performance in syndromes characterized by regionally specific atrophy patterns. Whereas diseases generally could be classified vs controls more correctly with increasing severity and duration, differentiation between diseases was optimal in disease-specific windows of severity and duration. DISCUSSION: Results suggest that automated methods applied to MR imaging data can support physicians in diagnosis of dementia syndromes. It is particularly relevant for orphan diseases beside frequent syndromes such as Alzheimer's disease.

Heart failure decouples the precuneus in interaction with social cognition and executive functions.

Aging increases the risk to develop Alzheimer's disease. Cardiovascular diseases might accelerate this process. Our study aimed at investigating the impact of heart failure on brain connectivity using functional magnetic resonance imaging at resting state. Here we show brain connectivity alterations related to heart failure and cognitive performance. Heart failure decreases brain connectivity in the precuneus. Precuneus dysconnectivity was associated with biomarkers of heart failure-left ventricular ejection fraction and N-terminal prohormone of brain natriuretic peptide-and cognitive performance, predominantly executive function. Meta-analytical data-mining approaches-conducted in the BrainMap and Neurosynth databases-revealed that social and executive cognitive functions are mainly associated with those neural networks. Remarkably, the precuneus, as identified in our study in a mid-life cohort, represents one central functional hub affected by Alzheimer's disease. A long-term follow-up investigation in our cohort after approximately nine years revealed more severe cognitive impairment in the group with heart failure than controls, where social cognition was the cognitive domain mainly affected, and not memory such as in Alzheimer's disease. In sum, our results indicate consistently an association between heart failure and decoupling of the precuneus from other brain regions being associated with social and executive functions. Further longitudinal studies are warranted elucidating etiopathological mechanisms.

Visuo-motor transformations in the intraparietal sulcus mediate the acquisition of endovascular medical skill.

Performing endovascular medical interventions safely and efficiently requires a diverse set of skills that need to be practised in dedicated training sessions. Here, we used multimodal magnetic resonance (MR) imaging to determine the structural and functional plasticity and core skills associated with skill acquisition. A training group learned to perform a simulator-based endovascular procedure, while a control group performed a simplified version of the task; multimodal MR images were acquired before and after training. Using a well-controlled interaction design, we found strong multimodal evidence for the role of the intraparietal sulcus (IPS) in endovascular skill acquisition that is in line with previous work implicating the structure in visuospatial transformations including simple visuo-motor and mental rotation tasks. Our results provide a unique window into the multimodal nature of rapid structural and functional plasticity of the human brain while learning a multifaceted and complex clinical skill. Further, our results provide a detailed description of the plasticity process associated with endovascular skill acquisition and highlight specific facets of skills that could enhance current medical pedagogy and be useful to explicitly target during clinical resident training.

Restoration of functional network state towards more physiological condition as the correlate of clinical effects of pallidal deep brain stimulation in dystonia.

BACKGROUND: Deep brain stimulation of the internal globus pallidus (GPi DBS) is an invasive therapeutic modality intended to retune abnormal central nervous system patterns and relieve the patient of dystonic or other motor symptoms. OBJECTIVES: The aim of the presented research was to determine the neuroanatomical signature of GPi DBS modulation and its association with the clinical outcome. METHODS: This open-label fixed-order study with cross-sectional validation against healthy controls analysed the resting-state functional MRI activity changes induced by GPi DBS in 18 dystonia patients of heterogeneous aetiology, focusing on both global (full brain) and local connectivity (local signal homogeneity). RESULTS: Compared to the switched-off state, the activation of GPi DBS led to the restoration of global subcortical connectivity patterns (in both putamina, diencephalon and brainstem) towards those of healthy controls, with positive direct correlation over large-scale cortico-basal ganglia-thalamo-cortical and cerebellar networks with the clinical improvement. Nonetheless, on average, GPi DBS also seemed to bring local connectivity both in the cortical and subcortical regions farther away from the state detected in healthy controls. Interestingly, its correlation with clinical outcome showed that in better DBS responders, local connectivity defied this effect and approached healthy controls. CONCLUSIONS: All in all, the extent of restoration of both these main metrics of interest towards the levels found in healthy controls clearly correlated with the clinical improvement, indicating that the restoration of network state towards more physiological condition may be a precondition for successful GPi DBS outcome in dystonia.

Increased Serum NSE and S100B Indicate Neuronal and Glial Alterations in Subjects Under 71 Years With Mild Neurocognitive Disorder/Mild Cognitive Impairment.

Background: Mild cognitive impairment (MCI) is considered a pre-stage of different dementia syndromes. Despite diagnostic criteria refined by DSM-5 and a new term for MCI - "mild neurocognitive disorder" (mild NCD) - this diagnosis is still based on clinical criteria. Methods: To link mild NCD to the underlying pathophysiology we assessed the degree of white matter hyperintensities (WMH) in the brain and peripheral biomarkers for neuronal integrity (neuron-specific enolase, NSE), plasticity (brain-derived neurotrophic factor, BDNF), and glial function (S100B) in 158 community-dwelling subjects with mild NCD and 82 healthy controls. All participants (63-79 years old) were selected from the Leipzig-population-based study of adults (LIFE). Results: Serum S100B levels were increased in mild NCD in comparison to controls (p = 0.007). Serum NSE levels were also increased but remained non-significant after Bonferroni-Holm correction (p = 0.04). Furthermore, age by group interaction was significant for S100B. In an age-stratified sub-analysis, NSE and S100B were higher in younger subjects with mild NCD below 71 years of age. Some effects were inconsistent after controlling for potentially confounding factors. The discriminatory power of the two biomarkers NSE and S100B was insufficient to establish a pathologic threshold for mild NCD. In subjects with mild NCD, WMH load correlated with serum NSE levels (r = 0.20, p = 0.01), independently of age. Conclusion: Our findings might indicate the presence of neuronal (NSE) and glial (S100B) injury in mild NCD. Future studies need to investigate whether younger subjects with mild NCD with increased biomarker levels are at risk of developing major NCD.

Exploring Links Between Psychosis and Frontotemporal Dementia Using Multimodal Machine Learning: Dementia Praecox Revisited.

Importance: The behavioral and cognitive symptoms of severe psychotic disorders overlap with those seen in dementia. However, shared brain alterations remain disputed, and their relevance for patients in at-risk disease stages has not been explored so far. Objective: To use machine learning to compare the expression of structural magnetic resonance imaging (MRI) patterns of behavioral-variant frontotemporal dementia (bvFTD), Alzheimer disease (AD), and schizophrenia; estimate predictability in patients with bvFTD and schizophrenia based on sociodemographic, clinical, and biological data; and examine prognostic value, genetic underpinnings, and progression in patients with clinical high-risk (CHR) states for psychosis or recent-onset depression (ROD). Design, Setting, and Participants: This study included 1870 individuals from 5 cohorts, including (1) patients with bvFTD (n = 108), established AD (n = 44), mild cognitive impairment or early-stage AD (n = 96), schizophrenia (n = 157), or major depression (n = 102) to derive and compare diagnostic patterns and (2) patients with CHR (n = 160) or ROD (n = 161) to test patterns' prognostic relevance and progression. Healthy individuals (n = 1042) were used for age-related and cohort-related data calibration. Data were collected from January 1996 to July 2019 and analyzed between April 2020 and April 2022. Main Outcomes and Measures: Case assignments based on diagnostic patterns; sociodemographic, clinical, and biological data; 2-year functional outcomes and genetic separability of patients with CHR and ROD with high vs low pattern expression; and pattern progression from baseline to follow-up MRI scans in patients with nonrecovery vs preserved recovery. Results: Of 1870 included patients, 902 (48.2%) were female, and the mean (SD) age was 38.0 (19.3) years. The bvFTD pattern comprising prefrontal, insular, and limbic volume reductions was more expressed in patients with schizophrenia (65 of 157 [41.2%]) and major depression (22 of 102 [21.6%]) than the temporo-limbic AD patterns (28 of 157 [17.8%] and 3 of 102 [2.9%], respectively). bvFTD expression was predicted by high body mass index, psychomotor slowing, affective disinhibition, and paranoid ideation (R2 = 0.11). The schizophrenia pattern was expressed in 92 of 108 patients (85.5%) with bvFTD and was linked to the C9orf72 variant, oligoclonal banding in the cerebrospinal fluid, cognitive impairment, and younger age (R2 = 0.29). bvFTD and schizophrenia pattern expressions forecasted 2-year psychosocial impairments in patients with CHR and were predicted by polygenic risk scores for frontotemporal dementia, AD, and schizophrenia. Findings were not associated with AD or accelerated brain aging. Finally, 1-year bvFTD/schizophrenia pattern progression distinguished patients with nonrecovery from those with preserved recovery. Conclusions and Relevance: Neurobiological links may exist between bvFTD and psychosis focusing on prefrontal and salience system alterations. Further transdiagnostic investigations are needed to identify shared pathophysiological processes underlying the neuroanatomical interface between the 2 disease spectra.

Advantages of virtual reality for the participative design of work processes: An integrative perspective.

BACKGROUND: The participative design of work processes is hampered by as-yet unresolved challenges. A root cause is seen in high information-pass-on-barriers. Virtual Reality (VR) may have a significant potential to overcome these challenges. Yet, there is no systematic understanding of which advantages provided by VR can support the participative design of work processes. OBJECTIVE: The present study aims to assess the potential of VR to support the participative design of work processes by conducting an integrative literature review identifying the advantages of VR in general work contexts and mapping them to known challenges in participative design of work processes. METHODS: The integrative literature review was conducted based on 268 sources of which 52 were considered for an in-depth analysis of the advantages offered by VR. RESULTS: The resulting conceptual framework consisted of 13 characteristic-related advantages (e.g., immersion, interactivity, flexibility) and 10 effect-related advantages (e.g., attractivity, involvement, cost efficiency) which readily address known challenges in the participative design of work processes. CONCLUSION: Mapping the advantages of VR to the challenges in participative design of work processes revealed a substantial potential of VR to overcome high information-pass-on-barriers. As such, employing VR in work process design initiatives represents a fruitful avenue for the promotion of prevention and employee health.

Comparative analysis of machine learning algorithms for multi-syndrome classification of neurodegenerative syndromes.

IMPORTANCE: The entry of artificial intelligence into medicine is pending. Several methods have been used for the predictions of structured neuroimaging data, yet nobody compared them in this context. OBJECTIVE: Multi-class prediction is key for building computational aid systems for differential diagnosis. We compared support vector machine, random forest, gradient boosting, and deep feed-forward neural networks for the classification of different neurodegenerative syndromes based on structural magnetic resonance imaging. DESIGN, SETTING, AND PARTICIPANTS: Atlas-based volumetry was performed on multi-centric T1-weighted MRI data from 940 subjects, i.e., 124 healthy controls and 816 patients with ten different neurodegenerative diseases, leading to a multi-diagnostic multi-class classification task with eleven different classes. INTERVENTIONS: N.A. MAIN OUTCOMES AND MEASURES: Cohen's kappa, accuracy, and F1-score to assess model performance. RESULTS: Overall, the neural network produced both the best performance measures and the most robust results. The smaller classes however were better classified by either the ensemble learning methods or the support vector machine, while performance measures for small classes were comparatively low, as expected. Diseases with regionally specific and pronounced atrophy patterns were generally better classified than diseases with widespread and rather weak atrophy. CONCLUSIONS AND RELEVANCE: Our study furthermore underlines the necessity of larger data sets but also calls for a careful consideration of different machine learning methods that can handle the type of data and the classification task best.

Symptom-severity-related brain connectivity alterations in functional movement disorders.

BACKGROUND: Functional movement disorders, a common cause of neurological disabilities, can occur with heterogeneous motor manifestations including functional weakness. However, the underlying mechanisms related to brain function and connectivity are unknown. OBJECTIVE: To identify brain connectivity alterations related to functional weakness we assessed network centrality changes in a group of patients with heterogeneous motor manifestations using task-free functional MRI in combination with different network centrality approaches. METHODS: Task-free functional MRI was performed in 48 patients with heterogeneous motor manifestations including 28 patients showing functional weakness and 65 age- and sex-matched healthy controls. Functional connectivity differences were assessed using different network centrality approaches, i.e. global correlation, eigenvector centrality, and intrinsic connectivity. Motor symptom severity was assessed using The Simplified Functional Movement Disorders Rating Scale and correlated with network centrality. RESULTS: Comparing patients with and without functional weakness showed significant network centrality differences in the left temporoparietal junction and precuneus. Patients with functional weakness showed increased centrality in the same anatomical regions when comparing functional weakness with healthy controls. Moreover, in the same regions, patients with functional weakness showed a positive correlation between motor symptom severity and network centrality. This correlation was shown to be specific to functional weakness with an interaction analysis, confirming a significant difference between patients with and without functional weakness. CONCLUSIONS: We identified the temporoparietal junction and precuneus as key regions involved in brain connectivity alterations related to functional weakness. We propose that both regions may be promising targets for phenotype-specific non-invasive brain stimulation.

Decreased thalamo-cortico connectivity during an implicit sequence motor learning task and 7 days escitalopram intake.

Evidence suggests that selective serotonin reuptake inhibitors (SSRIs) reorganize neural networks via a transient window of neuroplasticity. While previous findings support an effect of SSRIs on intrinsic functional connectivity, little is known regarding the influence of SSRI-administration on connectivity during sequence motor learning. To investigate this, we administered 20 mg escitalopram or placebo for 1-week to 60 healthy female participants undergoing concurrent functional magnetic resonance imaging and sequence motor training in a double-blind randomized controlled design. We assessed task-modulated functional connectivity with a psycho-physiological interaction (PPI) analysis in the thalamus, putamen, cerebellum, dorsal premotor, primary motor, supplementary motor, and dorsolateral prefrontal cortices. Comparing an implicit sequence learning condition to a control learning condition, we observed decreased connectivity between the thalamus and bilateral motor regions after 7 days of escitalopram intake. Additionally, we observed a negative correlation between plasma escitalopram levels and PPI connectivity changes, with higher escitalopram levels being associated with greater thalamo-cortico decreases. Our results suggest that escitalopram enhances network-level processing efficiency during sequence motor learning, despite no changes in behaviour. Future studies in more diverse samples, however, with quantitative imaging of neurochemical markers of excitation and inhibition, are necessary to further assess neural responses to escitalopram.

A single dose of escitalopram blunts the neural response in the thalamus and caudate during monetary loss.

Background: Selective serotonin reuptake inhibitors (SSRIs) show acute effects on the neural processes associated with negative affective bias in healthy people and people with depression. However, whether and how SSRIs also affect reward and punishment processing on a similarly rapid time scale remains unclear. Methods: We investigated the effects of an acute and clinically relevant dose (20 mg) of the SSRI escitalopram on brain response during reward and punishment processing in 19 healthy participants. In a doubleblind, placebo-controlled study using functional MRI, participants performed a well-established monetary reward task at 3 time points: at baseline; after receiving placebo or escitalopram; and after receiving placebo or escitalopram following an 8-week washout period. Results: Acute escitalopram administration reduced blood-oxygen-level-dependent (BOLD) response during punishment feedback in the right thalamus (family-wise error corrected [FWE] p = 0.013 at peak level) and the right caudate head (pFWE = 0.011 at peak level) compared to placebo. We did not detect any significant BOLD changes during reward feedback. Limitations: We included only healthy participants, so interpretation of findings are limited to the healthy human brain and require future testing in patient populations. The paradigm we used was based on monetary stimuli, and results may not be generalizable to other forms of reward. Conclusion: Our findings extend theories of rapid SSRI action on the neural processing of rewarding and aversive stimuli and suggest a specific and acute effect of escitalopram in the punishment neurocircuitry.

SERIAL-ORDER recall in working memory across the cognitive spectrum of Parkinson's disease and neuroimaging correlates.

We sought to determine if Parkinson's disease (PD) with mild cognitive impairment (MCI) is associated with a greater SERIAL-ORDER (mental manipulation) than ANY-ORDER (auditory span, storage) deficit in working memory (WM). We investigated WM combining neuropsychological measures with the study of brain functional connectivity. A cohort of 160 patients with idiopathic PD, classified as PD-MCI (n = 87) or PD with normal cognition (PD-NC; n = 73), and 70 matched healthy controls were studied. Verbal WM was assessed with the Backward Digit Span Task (BDT; Lamar et al., 2007, Neuropsychologia, 45, 245), measuring SERIAL-ORDER and ANY-ORDER recall. Resting-state MRI data were collected for 15 PD-MCI, 15 PD-NC and 30 controls. Hypothesis-driven seed-based functional connectivity of the dorsolateral prefrontal cortex (DLPFC) was compared between the three groups and correlated with BDT performance. We found the main effect of the test (impairment in SERIAL ORDER > ANY ORDER) and group ((NC = PD-NC) > PD-MCI) in BDT performance that was even more pronounced in SERIAL ORDER when controlling for ANY ORDER variability but not vice versa. Furthermore, PD-MCI compared to other groups were characterized by the functional disconnection between the bilateral DLPFC and the cerebellum. In functional correlations, DLPFC connectivity was positively related to both SERIAL- and ANY-ORDER performance. In conclusion, PD-MCI patients evidenced greater SERIAL-ORDER (manipulation and cognitive control) than ANY-ORDER (storage) working memory impairment than PD-NC and controls with a disrupted DLPFC resting-state connectivity that was also related to the verbal WM performance.

Modulation of premotor cortex response to sequence motor learning during escitalopram intake.

The contribution of selective serotonin reuptake inhibitors to motor learning by inducing motor cortical plasticity remains controversial given diverse findings from positive preclinical data to negative findings in recent clinical trials. To empirically address this translational disparity, we use functional magnetic resonance imaging in a double-blind, randomized controlled study to assess whether 20 mg escitalopram improves sequence-specific motor performance and modulates cortical motor response in 64 healthy female participants. We found decreased left premotor cortex responses during sequence-specific learning performance comparing single dose and steady escitalopram state. Escitalopram plasma levels negatively correlated with the premotor cortex response. We did not find evidence in support of improved motor performance after a week of escitalopram intake. These findings do not support the conclusion that one week escitalopram intake increases motor performance but could reflect early adaptive plasticity with improved neural processing underlying similar task performance when steady peripheral escitalopram levels are reached.