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The brain's default mode network (DMN) and the executive control network (ECN) switch engagement are influenced by the ventral attention network (VAN). Alterations in resting‐state functional connectivity (RSFC) within this so‐called triple network have been demonstrated in patients with major depressive disorder (MDD) or anxiety disorders (ADs). This study investigated alterations in the RSFC in patients with comorbid MDD and ADs to better understand the pathophysiology of this prevalent group of patients. Sixty‐eight participants (52.9% male, mean age 35.3 years), consisting of 25 patients with comorbid MDD and ADs (MDD + AD), 20 patients with MDD only (MDD) and 23 healthy controls (HCs) were investigated clinically and with 3T resting‐state fMRI. RSFC utilizing a seed‐based approach within the three networks belonging to the triple network was compared between the groups. Compared with HC, MDD + AD showed significantly reduced RSFC between the ECN and the VAN, the DMN and the VAN and within the ECN. No differences could be found for the MDD group compared with both other groups. Furthermore, symptom severity and medication status did not affect RSFC values. The results of this study show a distinct set of alterations of RSFC for patients with comorbid MDD and AD compared with HCs. This set of dysfunctions might be related to less adequate switching between the DMN and the ECN as well as poorer functioning of the ECN. This might contribute to additional difficulties in engaging and utilizing consciously controlled emotional regulation strategies. [ABSTRACT FROM AUTHOR]

Major Depression (MDD) and anxiety disorders are stress-related disorders that share pathophysiological mechanisms. There is evidence for alterations of glutamate-glutamine, N-acetylaspartate (NAA) and GABA in the anterior cingulate cortex (ACC), a stress-sensitive region affected by hypothalamic-pituitary-adrenal axis (HPA). The aim was to investigate metabolic alterations in the ACC and whether hair cortisol, current stress or early life adversity predict them. We investigated 22 patients with MDD and comorbid anxiety disorder and 23 healthy controls. Proton magnetic resonance spectroscopy was performed with voxels placed in pregenual (pg) and dorsal (d) ACC in 3 T. Analysis of hair cortisol was performed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The N-acetylaspartate/Creatin ratio (NAA/Cr) was reduced in patients in both pgACC (p =.040) and dACC (p =.016). A significant interactive effect of diagnosis and cortisol on both pg-NAA/Cr (F = 5.00, p =.033) and d-NAA/Cr (F = 7.86, p =.009) was detected, whereby in controls cortisol was positively correlated with d-NAA/Cr (r = 0.61, p =.004). Our results suggest a relationship between NAA metabolism in ACC and HPA axis activity as represented by long-term cortisol output. [ABSTRACT FROM AUTHOR]

Background: Inflammation has been described as a key pathogenic event in Alzheimer's disease (AD), downstream of amyloid and tau pathology. Preclinical and clinical data suggest that the cholinergic basal forebrain may moderate inflammatory response to different pathologies.Objective: To study the association of cholinergic basal forebrain volume and functional connectivity with measures of neuroinflammation in people from the AD spectrum.Methods: We studied 261 cases from the DELCODE cohort, including people with subjective cognitive decline, mild cognitive impairment, AD dementia, first degree relatives, and healthy controls. Using Bayesian ANCOVA, we tested associations of MRI indices of cholinergic basal forebrain volume and functional connectivity with cerebrospinal fluid (CSF) levels of sTREM2 as a marker of microglia activation, and serum levels of complement C3. Using Bayesian elastic net regression, we determined associations between basal forebrain measures and a large inflammation marker panel from CSF and serum.Results: We found anecdotal to moderate evidence in favor of the absence of an effect of basal forebrain volume and functional connectivity on CSF sTREM2 and serum C3 levels both in Aβ42/ptau-positive and negative cases. Bayesian elastic net regression identified several CSF and serum markers of inflammation that were associated with basal forebrain volume and functional connectivity. The effect sizes were moderate to small.Conclusion: Our data-driven analyses generate the hypothesis that cholinergic basal forebrain may be involved in the neuroinflammation response to Aβ42 and phospho-tau pathology in people from the AD spectrum. This hypothesis needs to be tested in independent samples. [ABSTRACT FROM AUTHOR]

Background: The NIA‐AA proposed ATN (Amyloid/Tau/Neurodegeneration) as a classification system for AD pathology. The Amyloid Cascade Hypothesis (ACH) implies a sequence across ATN groups that patients might undergo during transition from healthy towards AD: A‐T‐N‐→A+T‐N‐→A+T+N‐→A+T+N+. Here we assess the evidence for monotonic brain volume decline for this particular (Amyloid‐conversion first, Tau‐conversion second, N‐conversion last; therefore ‘ATN’) and alternative progressions (ANT, TAN, TNA, NAT, NTA) using Voxel‐based Morphometry (VBM) of brain anatomy in a large MRI sample. Method: We used the DELCODE cohort of 437 subjects (49% female) which underwent lumbar puncture, MRI scanning and neuropsychological assessment. ATN classification was performed using (A+/‐) CSF‐Abeta42over40, (T+/‐) CSF‐phospho‐Tau, and (N+/‐) adjusted hippocampal volume. We compared voxel‐based model evidence for monotonic decline of gray matter volume across various sequences over ATN groups accounting for age, sex, education, TIV and WMH. The evidence of each progression was assessed using the Bayesian Information Criterion on voxel‐ and ROI‐level. First, face validity of the ACH transition trajectory A‐T‐N‐→A+T‐N‐→A+T+N‐→A+T+N+ for VBM was compared against 23 biologically less plausible (permuted) sequences among AD‐continuum ATN groups. Then we evaluated the evidence for 6 brain volume progressions from A‐T‐N‐ towards A+T+N+ (ATN, ANT, TAN, TNA, NAT, NTA) including also non‐AD continuum ATN groups. Result: The ACH‐based progression A‐T‐N‐→A+T‐N‐→A+T+N‐→A+T+N+ is in line with cognitive decline and clinical diagnosis (Figure 1&2). It also has highest evidence in 9% of the gray matter voxels (especially MTL; Figure 3&4). Many (especially cortical) regions were compatible with alternative non‐monotonic volume progressions (‘AP 1’: 16%, ‘AP 2’: 14%; see Figure 3) over ACH progression sequence, compatible with early amyloid‐related tissue expansion or sampling effects due to brain‐reserve (Figure 5). Volume decline in 65% of voxels was more compatible with ATN/ANT progression (A flips first) when compared to alternative sequences (TAN, TNA, NAT, NTA). Conclusion: Early Amyloid status conversion (before Tau and Neurodegeneration) is compatible with brain volume loss observed during AD progression. The ATN classification and the ACH are compatible with monotonic progress of MTL atrophy. [ABSTRACT FROM AUTHOR]

Background: The hippocampus and its subfields (HippSub) are reported to be diminished in patients with Alzheimer's disease (AD), bipolar disorder (BD), and major depressive disorder (MDD). We examined these groups vs healthy controls (HC) to reveal HippSub alterations between diseases. Methods: We segmented 3T-MRI T2-weighted hippocampal images of 67 HC, 58 BD, and MDD patients from the AFFDIS study and 137 patients from the DELCODE study assessing cognitive decline, including subjective cognitive decline (SCD), amnestic mild cognitive impairment (aMCI), and AD, via Free Surfer 6.0 to compare volumes across groups. Results: Groups differed significantly in several HippSub volumes, particularly between patients with AD and mood disorders. In comparison to HC, significant lower volumes appear in aMCI and AD groups in specific subfields. Smaller volumes in the left presubiculum are detected in aMCI and AD patients, differing from the BD group. A significant linear regression is seen between left hippocampus volume and duration since the first depressive episode. Conclusions: HippSub volume alterations were observed in AD, but not in early-onset MDD and BD, reinforcing the notion of different neural mechanisms in hippocampal degeneration. Moreover, duration since the first depressive episode was a relevant factor explaining the lower left hippocampal volumes present in groups. [ABSTRACT FROM AUTHOR]

Background: Neuroimaging markers based on MRI often provide better prediction than traditional neuropsychological scores. With advancements of machine learning, data patterns may offer opportunities to personalize clinical practice that leads to better outcomes for patients at risk of dementia such as Alzheimer’s disease (AD) (Davatzikos et al., 2019). AD is a multifactorial process associated with ageing, brain atrophy, genes, proteins, vascular risk, and brain state activity (Frisoni et al., 2010). These processes do covary and interact in a complex fashion which needs to be accounted when aiming at predicting clinical outcomes for staging and stratification of disease‐modifying treatments. Method: In our probabilistic predictive framework we focus on data from the DZNE DELCODE cohort (Jessen et al., 2018) consisting of T1‐weighted and FLAIR images to assess distributed patterns of Voxel‐based Morphometry (VBM) and White Matter Lesions for 929 subjects; subject‐specific demographics (age, sex, education) and available CSF biomarkers for 438 subjects. We developed a machine learning framework for brain‐based predictions of (A) memory performance (Wolfsgruber et al., 2020) and (B) CSF Amyloid 42/40 and p‐tau biomarker status using a Gaussian process multi‐kernel (GP‐MKL) learning approach (Rasmussen & Williams, 2006). The proposed GP‐MKL model combines multiple features (atrophy patterns, demographics age, sex, education, white matter lesions volume & apoe4) expected to characterize the transition from healthy ageing towards dementia in terms of cognitive symptoms and biomarker status (Figure 1). We evaluate predictive models and different feature combinations using 10‐fold cross‐validation. Result: The framework enabled optimal individual prediction of memory performance (highest correlation true vs. predicted of r = 0.751 ± 0.082, R2 = 0.56, Fig. 2) using a combination of demographics, brain tissue segments (GM & CSF) & CSF biomarkers (Aß42/40 & p‐tau). When estimating the CSF biomarker positivity, the AUC‐ROC score achieved 0.735 for Aß42/40 (Fig. 4A) and 0.802 for p‐tau (Fig. 4B) using a combination of brain tissue segments (GM & CSF), demographics, and cognitive testing. Conclusion: In conclusion, multiple domains and imaging facets contribute to reliable estimation of individual cognitive memory performance and biomarker positivity in dementia and enable promising predictive technologies for staging and treatment stratification. [ABSTRACT FROM AUTHOR]

Mnemonic discrimination, the ability to distinguish similar events in memory, relies on subregions in the human medial temporal lobes (MTLs). Tau pathology is frequently found within the MTL of older adults and therefore likely to affect mnemonic discrimination, even in healthy older individuals. The MTL subregions that are known to be affected early by tau pathology, the perirhinal-transentorhinal region (area 35) and the anterior-lateral entorhinal cortex (alEC), have recently been implicated in the mnemonic discrimination of objects rather than scenes. Here we used an object-scene mnemonic discrimination task in combination with fMRI recordings and analyzed the relationship between subregional MTL activity, memory performance, and levels of total and phosphorylated tau as well as Aβ42/40 ratio in CSF. We show that activity in alEC was associated with mnemonic discrimination of similar objects but not scenes in male and female cognitively unimpaired older adults. Importantly, CSF tau levels were associated with increased fMRI activity in the hippocampus, and both increased hippocampal activity as well as tau levels were associated with mnemonic discrimination of objects, but again not scenes. This suggests that dysfunction of the alEC-hippocampus object mnemonic discrimination network might be a marker for tau-related cognitive decline. [ABSTRACT FROM AUTHOR]

Diffusion changes as determined by diffusion tensor imaging are potential indicators of microstructural lesions in people with mild cognitive impairment (MCI), prodromal Alzheimer's disease (AD), and AD dementia. Here we extended the scope of analysis toward subjective cognitive complaints as a pre-MCI at risk stage of AD. In a cohort of 271 participants of the prospective DELCODE study, including 93 healthy controls and 98 subjective cognitive decline (SCD), 45 MCI, and 35 AD dementia cases, we found reductions of fiber tract integrity in limbic and association fiber tracts in MCI and AD dementia compared with controls in a tract-based analysis (p < 0.05, family wise error corrected). In contrast, people with SCD showed spatially restricted white matter alterations only for the mode of anisotropy and only at an uncorrected level of significance. DTI parameters yielded a high cross-validated diagnostic accuracy of almost 80% for the clinical diagnosis of MCI and the discrimination of Aβ positive MCI cases from Aβ negative controls. In contrast, DTI parameters reached only random level accuracy for the discrimination between Aβ positive SCD and control cases from Aβ negative controls. These findings suggest that in prodromal stages of AD, such as in Aβ positive MCI, multicenter DTI with prospectively harmonized acquisition parameters yields diagnostic accuracy meeting the criteria for a useful biomarker. In contrast, automated tract-based analysis of DTI parameters is not useful for the identification of preclinical AD, including Aβ positive SCD and control cases. [ABSTRACT FROM AUTHOR]

Introduction: Subjective cognitive decline (SCD) can represent a preclinical stage of Alzheimer's disease. Diffusion tensor imaging (DTI) could aid an early diagnosis, yet only few monocentric DTI studies in SCD have been conducted, reporting heterogeneous results. We investigated microstructural changes in SCD in a larger, multicentric cohort. Methods: 271 participants with SCD, mild cognitive impairment (MCI) or Alzheimer's dementia (AD) and healthy controls (CON) were included, recruited prospectively at nine centers of the observational DELCODE study. DTI was acquired using identical protocols. Using voxel-based analyses, we investigated fractional anisotropy (FA), mean diffusivity (MD) and mode (MO) in the white matter (WM). Discrimination accuracy was determined by cross-validated elastic-net penalized regression. Center effects were explored using variance analyses. Results: MO and FA were lower in SCD compared to CON in several anterior and posterior WM regions, including the anterior corona radiata, superior and inferior longitudinal fasciculus, cingulum and splenium of the corpus callosum (p < 0.01, uncorrected). MD was higher in the superior and inferior longitudinal fasciculus, cingulum and superior corona radiata (p < 0.01, uncorrected). The cross-validated accuracy for discriminating SCD from CON was 67% (p < 0.01). As expected, the AD and MCI groups had higher MD and lower FA and MO in extensive regions, including the corpus callosum and temporal brain regions. Within these regions, center accounted for 3–15% of the variance. Conclusions: DTI revealed subtle WM alterations in SCD that were intermediate between those in MCI and CON and may be useful to detect individuals with an increased risk for AD in clinical studies. [ABSTRACT FROM AUTHOR]

Background: Subjective cognitive decline (SCD) has been proposed as an early symptomatic representation of Alzheimer's disease (AD). Per definition SCD implies patient's memory being subjectively impaired while broad neuropsychological indicators are still in normal range (Fig.1A). SCD might show early signs of atrophy in networks typically affected during AD disease progression. Among individuals with SCD, the prevalence of older adults who are on a declining AD trajectory are more frequent than in cognitively normal (CN) elderly. The key distinction between SCD and MCI would be a higher offset in memory ability in SCD and a larger proportion of individuals who have progressed further along the AD spectrum. This predicts that brain volume variability would be higher in SCD than in CN and non‐complaining older adults. Methods: We used sMRI at 3T to quantify anatomical differences using VBM in the DELCODE cohort in a subsample of 755 nondemented elderly (including 221 CN, 376 SCD & 158 MCI). We characterise memory ability using a composite score based on factor modelling (Wolfsgruber et al., under review) of neuropsychological tests. We explore group differences and the association of memory to local brain morphometry using GLM and SPM. We further analyze variability of local volumes across groups using voxel‐based Brown‐Forsythe‐Tests. Results: While there were significant volumetric differences of MCI but not in SCD as compared to healthy controls (Fig1 C left & right panel), volumetric variability (across subjects) was higher within the SCD (and MCI) as compared to CN in hippocampus (Fig. 2A). Individual differences in memory‐ability were positively associated with posterior hippocampal volume in SCD, but showed no association with brain volume in CN (Fig. 2B‐C). In MCI, variability in memory‐ability was also related to posterior hippocampal volume and in addition also to the volume of the anterior hippocampus and entorhinal cortex. Conclusions: In terms of morphometric variability and the association between morphometric measures and memory ability, the SCD group shows partial overlap with MCI and is distinct to cognitively normal, non‐complaining older adults. The posterior hippocampal region could be an area that explains interindividual memory variability in early stages of the Alzheimer's disease spectrum. [ABSTRACT FROM AUTHOR]

Background: Cognitive decline in Alzheimer's disease (AD) has been found associated with regional structural atrophy and functional disruption of neural networks, such as the default mode (DMN), visual (VN) and executive networks (EN) in structural and functional imaging (fMRI) studies, mostly using single test scores of cognitive performance among monocentric cohorts. In contrast to single test scores, cognitive domain composite scores could be more reliable than single test scores due to the reduction of measurement error. Using a multicentric resting state fMRI (rs‐fMRI) and cognitive domain approach, we provide a comprehensive description of the structural and functional correlates of the key cognitive domains of AD with a focus on visuo‐spatial deficits, which manifest in the early stages of the disease. Method: We analyzed MRI, rs‐fMRI and cognitive domain score data of 490 participants from the N700 cohort of the multicenter DELCODE study, including 54 people with Alzheimer's Dementia (AD), 86 with Mild Cognitive Impairment (MCI), 175 with Subjective Cognitive Decline (SCD), and 175 Healthy Controls (HC) (Table 1). Resulting cognitive domain composite scores (executive, visuo‐spatial, memory, working memory and language) from the DELCODE neuropsychological battery (DELCODE‐NP), were derived using confirmatory factor analysis. Statistical analysis examined the differences between diagnostic groups, and the association of composite scores with regional atrophy and network‐specific functional connectivity. Result: Cognitive performance significantly differed between diagnostic groups in AD‐spectrum (Table 2). Regional gray matter atrophy was associated with visuospatial and other cognitive impairments in AD‐spectrum (Figure 1). Patterns of network‐specific resting‐state functional connectivity (except VN) was associated with distinct cognitive impairments in AD‐spectrum (Figure 2). Conclusion: Robust associations between cognitive domain scores and both regional atrophy and network‐specific functional connectivity (except for VN), suggest the utility of the multicentric and cognitive domain approach towards explicating the relationship between imaging markers and cognition in AD‐spectrum. [ABSTRACT FROM AUTHOR]

Background: Alterations of intrinsic networks from resting state fMRI (rs-fMRI) have been suggested as functional biomarkers of Alzheimer's disease (AD).Objective: To determine the diagnostic accuracy of multicenter rs-fMRI for prodromal and preclinical stages of AD.Methods: We determined rs-fMRI functional connectivity based on Pearson's correlation coefficients and amplitude of low-frequency fluctuation in people with subjective cognitive decline, people with mild cognitive impairment, and people with AD dementia compared with healthy controls. We used data of 247 participants of the prospective DELCODE study, a longitudinal multicenter observational study, imposing a unified fMRI acquisition protocol across sites. We determined cross-validated discrimination accuracy based on penalized logistic regression to account for multicollinearity of predictors.Results: Resting state functional connectivity reached significant cross-validated group discrimination only for the comparison of AD dementia cases with healthy controls, but not for the other diagnostic groups. AD dementia cases showed alterations in a large range of intrinsic resting state networks, including the default mode and salience networks, but also executive and language networks. When groups were stratified according to their CSF amyloid status that was available in a subset of cases, diagnostic accuracy was increased for amyloid positive mild cognitive impairment cases compared with amyloid negative controls, but still inferior to the accuracy of hippocampus volume.Conclusion: Even when following a strictly harmonized data acquisition protocol and rigorous scan quality control, widely used connectivity measures of multicenter rs-fMRI do not reach levels of diagnostic accuracy sufficient for a useful biomarker in prodromal stages of AD. [ABSTRACT FROM AUTHOR]

A salience network (SN) anchored in the anterior insula (AI) and dorsal anterior cingulate cortex (dACC) plays a key role in switching between brain networks during salience detection and attention regulation. Previous fMRI studies have associated expectancy behaviors and SN activation with novelty seeking (NS) and reward dependence (RD) personality traits. To address the question of how functional connectivity (FC) in the SN is modulated by internal (expectancy-related) salience assignment and different personality traits, 68 healthy participants performed a salience expectancy task using functional magnetic resonance imaging, and psychophysiological interaction analysis (PPI) was conducted to determine salience-related connectivity changes during these anticipation periods. Correlation was then evaluated between PPI and personality traits, assessed using the temperament and character inventory of 32 male participants. During high salience expectancy, SN-seed regions showed reduced FC to visual areas and parts of the default mode network, but increased FC to the central executive network. With increasing NS, participants showed significantly increasing disconnection between right AI and middle cingulate cortex when expecting high-salience pictures as compared to low-salience pictures, while increased RD also predicted decreased right dACC and caudate FC for high salience expectancy. Our findings suggest a direct link between personality traits and internal salience processing mediated by differential network integration of the SN. SN activity and coordination may therefore be moderated by novelty seeking and reward dependency personality traits, which are associated with risk of addiction. Hum Brain Mapp 38:4064-4077, 2017. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

The large number of multicollinear regional features that are provided by resting state (rs) fMRI data requires robust feature selection to uncover consistent networks of functional disconnection in Alzheimer's disease (AD). Here, we compared elastic net regularized and classical stepwise logistic regression in respect to consistency of feature selection and diagnostic accuracy using rs-fMRI data from four centers of the "German resting-state initiative for diagnostic biomarkers" (psymri.org), comprising 53 AD patients and 118 age and sex matched healthy controls. Using all possible pairs of correlations between the time series of rs-fMRI signal from 84 functionally defined brain regions as the initial set of predictor variables, we calculated accuracy of group discrimination and consistency of feature selection with bootstrap cross-validation. Mean areas under the receiver operating characteristic curves as measure of diagnostic accuracy were 0.70 in unregularized and 0.80 in regularized regression. Elastic net regression was insensitive to scanner effects and recovered a consistent network of functional connectivity decline in AD that encompassed parts of the dorsal default mode as well as brain regions involved in attention, executive control, and language processing. Stepwise logistic regression found no consistent network of AD related functional connectivity decline. Regularized regression has high potential to increase diagnostic accuracy and consistency of feature selection from multicollinear functional neuroimaging data in AD. Our findings suggest an extended network of functional alterations in AD, but the diagnostic accuracy of rs-fMRI in this multicenter setting did not reach the benchmark defined for a useful biomarker of AD. [ABSTRACT FROM AUTHOR]

Attachment patterns influence actions, thoughts and feeling through a person's "inner working model". Speech charged with attachment-dependent content was proposed to modulate the activation of cognitive-emotional schemata in listeners. We performed a 7 Tesla rest-task-rest functional magnetic resonance imaging (fMRI)-experiment, presenting auditory narratives prototypical of dismissing attachment representations to investigate their effect on 23 healthy males. We then examined effects of participants' attachment style and childhood trauma on brain state changes using seed-based functional connectivity (FC) analyses, and finally tested whether subjective differences in responsivity to narratives could be predicted by baseline network states. In comparison to a baseline state, we observed increased FC in a previously described "social aversion network" including dorsal anterior cingulated cortex (dACC) and left anterior middle temporal gyrus (aMTG) specifically after exposure to insecure-dismissing attachment narratives. Increased dACC-seeded FC within the social aversion network was positively related to the participants' avoidant attachment style and presence of a history of childhood trauma. Anxious attachment style on the other hand was positively correlated with FC between the dACC and a region outside of the "social aversion network", namely the dorsolateral prefrontal cortex, which suggests decreased network segregation as a function of anxious attachment. Finally, the extent of subjective experience of friendliness towards the dismissing narrative was predicted by low baseline FC-values between hippocampus and inferior parietal lobule (IPL). Taken together, our study demonstrates an activation of networks related to social aversion in terms of increased connectivity after listening to insecure-dismissing attachment narratives. A causal interrelation of brain state changes and subsequent changes in social reactivity was further supported by our observation of direct prediction of neuronal responses by individual attachment and trauma characteristics and reversely prediction of subjective experience by intrinsic functional connections. We consider these findings of activation of within-network and between-network connectivity modulated by inter-individual differences as substantial for the understanding of interpersonal processes, particularly in clinical settings. [ABSTRACT FROM AUTHOR]

Background: Various psychiatric populations are currently investigated with resting state fMRI, with the aim of individualizing diagnostics and treatment options and improving treatment outcomes. Many of these studies are conducted in large naturalistic samples, providing rich insights regarding disease-related neural alterations, but with the common psychopharmacological medication limiting interpretations of the results. We therefore investigated the effects of common noradrenergic and anti-dopaminergic medications on local and global resting state activity (rs-activity) in healthy volunteers to further the understanding of the respective effects independent from disease-related alterations. Methods: Within a randomized, double-blind, placebo-controlled crossover design, we investigated 19 healthy male subjects by resting state fMRI after the intake of reboxetine (4 mg/d), amisulpride (200 mg/d), and placebo for 7 days each. Treatmentrelated differences in local and global rs-activity were measured by the fractional amplitude of low frequency fluctuations (fALFF) and resting state functional connectivity (rs-FC). Results: fALFF revealed alterations of local rs-activity within regions of the core noradrenergic pathway, including the locus coeruleus under reboxetine, correlated with its plasma levels. Moreover, reboxetine led to increased rs-FC between regions within this pathway, i.e. the locus coeruleus, tectum, thalamus, and amygdala. Amisulpride modulated local rs-activity of regions within the dopaminergic pathway, with the altered signal in the putamen correlating with amisulpride plasma levels. Correspondingly, amisulpride increased rs-FC between regions of the dopaminergic pathway comprising the substantia nigra and putamen. Conclusion: Our data provide evidence of how psychopharmacological agents alter local and global rs-activity within the respective neuroanatomical pathways in healthy subjects, which may help with interpreting data in psychiatric populations. [ABSTRACT FROM AUTHOR]

While antidepressants are supposed to exert similar effects on mood and drive via various mechanisms of action, diverging effects are observed regarding side-effects and accordingly on neural correlates of motivation, emotion, reward and salient stimuli processing as a function of the drugs impact on neurotransmission. In the context of erotic stimulation, a unidirectional modulation of attentional functioning despite opposite effects on sexual arousal has been suggested for the selective serotonin reuptake-inhibitor (SSRI) paroxetine and the selective dopamine and noradrenaline reuptake-inhibitor (SDNRI) bupropion. To further elucidate the effects of antidepressant-related alterations of neural attention networks, we investigated 18 healthy males under subchronic administration (7 d) of paroxetine (20 mg), bupropion (150 mg) and placebo within a randomized placebo-controlled cross-over double-blind functional magnetic resonance imaging (fMRI) design during an established preceding attention task. Neuropsychological effects beyond the fMRI-paradigm were assessed by measuring alertness and divided attention. Comparing preceding attention periods of salient vs. neutral pictures, we revealed congruent effects of both drugs vs. placebo within the anterior midcingulate cortex, dorsolateral prefrontal cortex, anterior prefrontal cortex, superior temporal gyrus, anterior insula and the thalamus. Relatively decreased activation in this network was paralleled by slower reaction times in the divided attention task in both verum conditions compared to placebo. Our results suggest similar effects of antidepressant treatments on behavioural and neural attentional functioning by diverging neurochemical pathways. Concurrent alterations of brain regions within a fronto-parietal and cingulo-opercular attention network for top-down control could point to basic neural mechanisms of antidepressant action irrespective of receptor profiles. [ABSTRACT FROM AUTHOR]

The thalamus, a crucial node in the well-described cortico-striatal-thalamo-cortical circuits, has been the focus of functional and structural imaging studies investigating human emotion, cognition and memory. Invasive work in animals and post-mortem investigations have revealed the rich cytoarchitectonics and functional specificity of the thalamus. Given current restrictions in the spatial resolution of non-invasive imaging modalities, there is, however, a translational gap between functional and structural information on these circuits in humans and animals as well as between histological and cellular evidence and their relationship to psychological functioning. With the advance of higher field strengths for MR approaches, better spatial resolution is now available promising to overcome this conceptual problem. We here review these two levels, which exist for both neuroscientific and clinical investigations, and then focus on current attempts to overcome conceptual boundaries of these observations with the help of ultra-high resolution imaging. [ABSTRACT FROM AUTHOR]

Background: Anosognosia, or lack of awareness of cognitive impairments, is a common phenomenon in Alzheimer's clinical syndrome (ACS). Not just patients with dementia(AD) but also patients with mild cognitive impairment(MCI) may have diminished awareness of their deficits. Previous studies have shown that anosognosia is associated with dysfunction and reduced connectivity in the default mode network of the brain and insula. However, less is known about the level of awareness and its neural correlations in individuals with subjective cognitive decline(SCD). This study investigated the underlying neural mechanisms of anosognosia at different stages of ACS. Method: 504 participants (59 AD, 88 MCI, 176 SCD and 181 healthy controls[HCs]) from the DELCODE, a longitudinal multicenter observational study, were included. Cognitive awareness was assessed with a discrepancy score between participants' report about their own cognitive abilities and report provided by informants. Resting‐state fMRI data of all subjects were analyzed and the fractional amplitude of low frequency fluctuations(fALFF) were calculated as an index of regional spontaneous neural activity. Voxel‐ and clusterwise correlations were conducted using SPM12, controlling for multiple comparisons(GRF). Age, gender and site (9 sites total) were controlled for in each statistical model. Result: Compared to HCs, subjects with SCD showed heightened awareness for cognitive changes and on the contrary, MCI and AD subjects had higher anosognosia scores. Within‐group comparisons revealed that MCI subjects with anosognosia had reduced neural activity in the left anterior insula compared to MCI subjects without anosognosia (GRF corrected, p<0.005). Moreover, SCD subjects with heightened awareness showed reduced right amygdala activity(GRF corrected, p<0.005), whereas higher activity was observed in the dorsomedial prefrontal cortex (dmPFC) compared to SCD subjects without heightened awareness(GRF corrected, p<0.001). Conclusion: This is the first study evaluating the association between cognitive awareness at different stages of ACS and regional neural activity using fALFF. Consistent with prior findings, MCI subjects with anosognosia showed reduced neural activity in the anterior insula. Heightened awareness in SCD was associated with higher activity in the dmPFC. Future work should examine the interplay between amyloid pathology and fALFF measures for cognitive awareness, in order to specify neural correlates of cognitive awareness in the Alzheimer's continuum. [ABSTRACT FROM AUTHOR]

Background: Early identification of individuals at risk of dementia is mandatory to implement prevention strategies and design clinical trials that target early disease stages. Subjective cognitive decline (SCD) and neuropsychiatric symptoms (NPS) have been proposed as potential markers for early manifestation of Alzheimer's disease (AD). We aimed to investigate the frequency of NPS in SCD, in other at-risk groups, in healthy controls (CO), and in AD patients, and to test the association of NPS with AD biomarkers, with a particular focus on cognitively unimpaired participants with or without SCD-related worries. Methods: We analyzed data of n = 687 participants from the German DZNE Longitudinal Cognitive Impairment and Dementia (DELCODE) study, including the diagnostic groups SCD (n = 242), mild cognitive impairment (MCI, n = 115), AD (n = 77), CO (n = 209), and first-degree relatives of AD patients (REL, n = 44). The Neuropsychiatric Inventory Questionnaire (NPI-Q), Geriatric Depression Scale (GDS-15), and Geriatric Anxiety Inventory (GAI-SF) were used to assess NPS. We examined differences of NPS frequency between diagnostic groups. Logistic regression analyses were carried out to further investigate the relationship between NPS and cerebrospinal fluid (CSF) AD biomarkers, focusing on a subsample of cognitively unimpaired participants (SCD, REL, and CO), who were further differentiated based on reported worries. Results: The numbers of reported NPS, depression scores, and anxiety scores were significantly higher in subjects with SCD compared to CO. The quantity of reported NPS in subjects with SCD was lower compared to the MCI and AD group. In cognitively unimpaired subjects with worries, low Aß42 was associated with higher rates of reporting two or more NPS (OR 0.998, 95% CI 0.996–1.000, p <.05). Conclusion: These findings give insight into the prevalence of NPS in different diagnostic groups, including SCD and healthy controls. NPS based on informant report seem to be associated with underlying AD pathology in cognitively unimpaired participants who worry about cognitive decline. Trial registration: German Clinical Trials Register DRKS00007966. Registered 4 May 2015. [ABSTRACT FROM AUTHOR]