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Functional connectivity has been observed to fluctuate across the course of a resting state scan, though the origins and functional relevance of this phenomenon remain to be shown. The present study explores the link between endogenous dynamics of functional connectivity and autonomic state in an eyes-closed resting condition. Using a sliding window analysis on resting state fMRI data from 35 young, healthy male subjects, we examined how heart rate variability (HRV) covaries with temporal changes in whole-brain functional connectivity with seed regions previously described to mediate effects of vigilance and arousal (amygdala and dorsal anterior cingulate cortex; dACC). We identified a set of regions, including brainstem, thalamus, putamen, and dorsolateral prefrontal cortex, that became more strongly coupled with the dACC and amygdala seeds during states of elevated HRV. Effects differed between high and low frequency components of HRV, suggesting specific contributions of parasympathetic and sympathetic tone on individual connections. Furthermore, dynamics of functional connectivity could be separated from those primarily related to BOLD signal fluctuations. The present results contribute novel information about the neural basis of transient changes of autonomic nervous system states, and suggest physiological and psychological components of the recently observed non-stationarity in resting state functional connectivity. ► HRV covaried with fluctuations in resting connectivity seeded from dACC and amygdala. ► Distinct effects were found between high-frequency and low-frequency HRV. ► Autonomic fluctuations may contribute to nonstationarity in resting connectivity.

Increasing preclinical and clinical evidence underscores the strong and rapid antidepressant properties of the glutamate-modulating NMDA receptor antagonist ketamine. Targeting the glutamatergic system might thus provide a novel molecular strategy for antidepressant treatment. Since glutamate is the most abundant and major excitatory neurotransmitter in the brain, pathophysiological changes in glutamatergic signaling are likely to affect neurobehavioral plasticity, information processing and large-scale changes in functional brain connectivity underlying certain symptoms of major depressive disorder. Using resting state functional magnetic resonance imaging (rsfMRI), the \"dorsal nexus \"(DN) was recently identified as a bilateral dorsal medial prefrontal cortex region showing dramatically increased depression-associated functional connectivity with large portions of a cognitive control network (CCN), the default mode network (DMN), and a rostral affective network (AN). Hence, Sheline and colleagues (2010) proposed that reducing increased connectivity of the DN might play a critical role in reducing depression symptomatology and thus represent a potential therapy target for affective disorders. Here, using a randomized, placebo-controlled, double-blind, crossover rsfMRI challenge in healthy subjects we demonstrate that ketamine decreases functional connectivity of the DMN to the DN and to the pregenual anterior cingulate (PACC) and medioprefrontal cortex (MPFC) via its representative hub, the posterior cingulate cortex (PCC). These findings in healthy subjects may serve as a model to elucidate potential biomechanisms that are addressed by successful treatment of major depression. This notion is further supported by the temporal overlap of our observation of subacute functional network modulation after 24 hours with the peak of efficacy following an intravenous ketamine administration in treatment-resistant depression.

IntroductionSubjective 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.Methods271 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.ResultsMO 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.ConclusionsDTI 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.

In Alzheimer’s disease (AD), a single-nucleotide polymorphism in the gene encoding brain-derived neurotrophic factor (BDNFVal66Met) is associated with worse impact of primary AD pathology (beta-amyloid, Aβ) on neurodegeneration and cognitive decline, rendering BDNFVal66Met an important modulating factor of cognitive impairment in AD. However, the effect of BDNFVal66Met on functional networks that may underlie cognitive impairment in AD is poorly understood. Using a cross-validation approach, we first explored in subjects with autosomal dominant AD (ADAD) from the Dominantly Inherited Alzheimer Network (DIAN) the effect of BDNFVal66Met on resting-state fMRI assessed functional networks. In seed-based connectivity analysis of six major large-scale networks, we found a stronger decrease of hippocampus (seed) to medial-frontal connectivity in the BDNFVal66Met carriers compared to BDNFVal homozogytes. BDNFVal66Met was not associated with connectivity in any other networks. Next, we tested whether the finding of more pronounced decrease in hippocampal-medial-frontal connectivity in BDNFVal66Met could be also found in elderly subjects with sporadically occurring Aβ, including a group with subjective cognitive decline (N = 149, FACEHBI study) and a group ranging from preclinical to AD dementia (N = 114, DELCODE study). In both of these independently recruited groups, BDNFVal66Met was associated with a stronger effect of more abnormal Aβ-levels (assessed by biofluid-assay or amyloid-PET) on hippocampal-medial-frontal connectivity decreases, controlled for hippocampus volume and other confounds. Lower hippocampal-medial-frontal connectivity was associated with lower global cognitive performance in the DIAN and DELCODE studies. Together these results suggest that BDNFVal66Met is selectively associated with a higher vulnerability of hippocampus-frontal connectivity to primary AD pathology, resulting in greater AD-related cognitive impairment.

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 (4mg/d), amisulpride (200mg/d), and placebo for 7 days each. Treatment-related 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.

Background Subjective cognitive decline (SCD) has been proposed as a pre-MCI at-risk condition of Alzheimer’s disease (AD). Current research is focusing on a refined assessment of specific SCD features associated with increased risk for AD, as proposed in the SCD-plus criteria. We developed a structured interview (SCD-I) for the assessment of these features and tested their relationship with AD biomarkers. Methods We analyzed data of 205 cognitively normal participants of the DELCODE study (mean age = 68.9 years; 52% female) with available CSF AD biomarkers (Aß-42, p-Tau181, Aß-42/Tau ratio, total Tau). For each of five cognitive domains (including memory, language, attention, planning, others), a study physician asked participants about the following SCD-plus features: the presence of subjective decline, associated worries, onset of SCD, feeling of worse performance than others of the same age group, and informant confirmation. We compared AD biomarkers of subjects endorsing each of these questions with those who did not, controlling for age. SCD was also quantified by two summary scores: the number of fulfilled SCD-plus features, and the number of domains with experienced decline. Covariate-adjusted linear regression analyses were used to test whether these SCD scores predicted abnormality in AD biomarkers. Results Lower Aß-42 levels were associated with a reported decline in memory and language abilities, and with the following SCD-plus features: onset of subjective decline within 5 years , confirmation of cognitive decline by an informant , and decline-related worries . Furthermore, both quantitative SCD scores were associated with lower Aß42 and lower Aß42/Tau ratio, but not with total Tau or p-Tau181. Conclusions Findings support the usefulness of a criterion-based interview approach to assess and quantify SCD in the context of AD and validate the current SCD-plus features as predictors of AD pathology. While some features seem to be more closely associated with AD biomarkers than others, aggregated scores over several SCD-plus features or SCD domains may be the best predictors of AD pathology.

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.

Thalamocortical loops, connecting functionally segregated, higher order cortical regions, and basal ganglia, have been proposed not only for well described motor and sensory regions, but also for limbic and prefrontal areas relevant for affective and cognitive processes. These functions are, however, more specific to humans, rendering most invasive neuroanatomical approaches impossible and interspecies translations difficult. In contrast, non-invasive imaging of functional neuroanatomy using fMRI allows for the development of elaborate task paradigms capable of testing the specific functionalities proposed for these circuits. Until recently, spatial resolution largely limited the anatomical definition of functional clusters at the level of distinct thalamic nuclei. Since their anatomical distinction seems crucial not only for the segregation of cognitive and limbic loops but also for the detection of their functional interaction during cognitive-emotional integration, we applied high resolution fMRI on 7 Tesla. Using an event-related design, we could isolate thalamic effects for preceding attention as well as experience of erotic stimuli. We could demonstrate specific thalamic effects of general emotional arousal in mediodorsal nucleus and effects specific to preceding attention and expectancy in intralaminar centromedian/parafascicular complex. These thalamic effects were paralleled by specific coactivations in the head of caudate nucleus as well as segregated portions of rostral or caudal cingulate cortex and anterior insula supporting distinct thalamo-striato-cortical loops. In addition to predescribed effects of sexual arousal in hypothalamus and ventral striatum, high resolution fMRI could extent this network to paraventricular thalamus encompassing laterodorsal and parataenial nuclei. We could lend evidence to segregated subcortical loops which integrate cognitive and emotional aspects of basic human behavior such as sexual processing.

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.

While some individuals age without pathological memory impairments, others develop age‐associated cognitive diseases. Since changes in cognitive function develop slowly over time in these patients, they are often diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. Thus, there is great need for the identification of inexpensive and minimal invasive approaches that could be used for screening with the aim to identify individuals at risk for cognitive decline that can then undergo further diagnostics and eventually stratified therapies. In this study, we use an integrative approach combining the analysis of human data and mechanistic studies in model systems to identify a circulating 3‐microRNA signature that reflects key processes linked to neural homeostasis and inform about cognitive status. We furthermore provide evidence that expression changes in this signature represent multiple mechanisms deregulated in the aging and diseased brain and are a suitable target for RNA therapeutics. SYNOPSIS Alzheimer’s disease (AD) is usually diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. This study aimed to identify a minimally invasive biomarker that can help to identify individuals at risk for cognitive decline before clinical manifestation. Circulating microRNAs are linked to cognitive function in young and healthy humans. A circulating 3‐microRNA signature is identified using a longitudinal mouse model of age‐associated memory decline. The expression of the 3‐microRNA signature is increased in patients with mild cognitive impairment (MCI) and is associated with future conversion from MCI to AD. Targeting all 3‐ microRNAs using anti‐miRs ameliorates cognitive decline in AD mice. Graphical Abstract Alzheimer’s disease (AD) is usually diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. This study aimed to identify a minimally invasive biomarker that can help to identify individuals at risk for cognitive decline before clinical manifestation.