Investigating the effects of the aging brain on real tool use performance-an fMRI study.

Introduction: Healthy aging affects several domains of cognitive and motor performance and is further associated with multiple structural and functional neural reorganization patterns. However, gap of knowledge exists, referring to the impact of these age-related alterations on the neural basis of tool use-an important, complex action involved in everyday life throughout the entire lifespan. The current fMRI study aims to investigate age-related changes of neural correlates involved in planning and executing a complex object manipulation task, further providing a better understanding of impaired tool use performance in apraxia patients. Methods: A balanced number of sixteen older and younger healthy adults repeatedly manipulated everyday tools in an event-related Go-No-Go fMRI paradigm. Results: Our data indicates that the left-lateralized network, including widely distributed frontal, temporal, parietal and occipital regions, involved in tool use performance is not subjected to age-related functional reorganization processes. However, age-related changes regarding the applied strategical procedure can be detected, indicating stronger investment into the planning, preparatory phase of such an action in older participants.

Broadly applicable methods for the detection of artefacts in electroencephalography acquired simultaneously with hemodynamic recordings.

Electroencephalography (EEG) data, acquired simultaneously with magnetic resonance imaging (MRI), must be corrected for artefacts related to MR gradient switches (GS) and the cardioballistic (CB) effect. Canonical approaches require additional signal acquisition for artefact detection (e.g., MR volume onsets, ECG), without which the EEG data would be rendered uncleanable from these artefacts.•We present two broadly applicable methods for artefact detection based on peak detection combined with temporal constraints with respect to periodicity directly from the EEG data itself; no additional signals are required. We validated the performance of our methods versus the two canonical approaches for detection of GS/CB artefact, respectively, on 26 healthy human EEG-functional MRI resting-state datasets. Utilising various performance metrics, we found our methods to perform as well as - and sometimes better than - the canonical standard approaches. With as little as one EEG channel recording, our methods can be applied to detect GS/CB artefacts in EEG data acquired simultaneously with MRI in the absence of MR volume onsets and/or an ECG recording. The detected artefact onsets can then be fed into the standard artefact correction software.

Frequency-specific coactivation patterns in resting-state and their alterations in schizophrenia: An fMRI study.

The resting-state human brain is a dynamic system that shows frequency-dependent characteristics. Recent studies demonstrate that coactivation pattern (CAP) analysis can identify recurring brain states with similar coactivation configurations. However, it is unclear whether and how CAPs depend on the frequency bands. The current study investigated the spatial and temporal characteristics of CAPs in the four frequency sub-bands from slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), slow-3 (0.073-0.198 Hz), to slow-2 (0.198-0.25 Hz), in addition to the typical low-frequency range (0.01-0.08 Hz). In the healthy subjects, six CAP states were obtained at each frequency band in line with our prior study. Similar spatial patterns with the typical range were observed in slow-5, 4, and 3, but not in slow-2. While the frequency increased, all CAP states displayed shorter persistence, which caused more between-state transitions. Specifically, from slow-5 to slow-4, the coactivation not only changed significantly in distributed cortical networks, but also increased in the basal ganglia as well as the amygdala. Schizophrenia patients showed significant alteration in the persistence of CAPs of slow-5. Using leave-one-pair-out, hold-out and resampling validations, the highest classification accuracy (84%) was achieved by slow-4 among different frequency bands. In conclusion, our findings provide novel information about spatial and temporal characteristics of CAP states at different frequency bands, which contributes to a better understanding of the frequency aspect of biomarkers for schizophrenia and other disorders.

Quantification of Kuramoto Coupling Between Intrinsic Brain Networks Applied to fMRI Data in Major Depressive Disorder.

Organized patterns of system-wide neural activity adapt fluently within the brain to adjust behavioral performance to environmental demands. In major depressive disorder (MD), markedly different co-activation patterns across the brain emerge from a rather similar structural substrate. Despite the application of advanced methods to describe the functional architecture, e.g., between intrinsic brain networks (IBNs), the underlying mechanisms mediating these differences remain elusive. Here we propose a novel complementary approach for quantifying the functional relations between IBNs based on the Kuramoto model. We directly estimate the Kuramoto coupling parameters (K) from IBN time courses derived from empirical fMRI data in 24 MD patients and 24 healthy controls. We find a large pattern with a significant number of Ks depending on the disease severity score Hamilton D, as assessed by permutation testing. We successfully reproduced the dependency in an independent test data set of 44 MD patients and 37 healthy controls. Comparing the results to functional connectivity from partial correlations (FC), to phase synchrony (PS) as well as to first order auto-regressive measures (AR) between the same IBNs did not show similar correlations. In subsequent validation experiments with artificial data we find that a ground truth of parametric dependencies on artificial regressors can be recovered. The results indicate that the calculation of Ks can be a useful addition to standard methods of quantifying the brain's functional architecture.

Segregated Co-activation Patterns in the Emergence of Decision Confidence During Visual Perception.

Visual metacognition-the introspection and evaluation of one's own visual perceptual processes-is measured through both decision confidence and "metacognitive efficiency." Metacognitive efficiency refers to an individual's ability to accurately judge incorrect and correct decisions through confidence ratings given their task performance. Previous imaging studies in humans and nonhuman primates reported widely distributed brain regions being involved in decision confidence and metacognition. However, the neural correlates of metacognition are remarkably inconsistent across studies concerning spatial outline. Therefore, this study investigates the neural correlates of visual metacognition by examining co-activation across regions that scale with visual decision confidence. We hypothesized that interacting processes of perceptual and metacognitive performance contribute to the arising decision confidence in distributed, but segregable co-activating brain regions. To test this hypothesis, we performed task-fMRI in healthy humans during a visual backward masking task with four-scale, post-decision confidence ratings. We measured blood oxygenation covariation patterns, which served as a physiological proxy for co-activation across brain regions. Decision confidence ratings and an individual's metacognitive efficiency served as behavioral measures for metacognition. We found three distinct co-activation clusters involved in decision confidence: the first included right-centered fronto-temporal-parietal regions, the second included left temporal and parietal regions, and the left basal forebrain (BF), and the third included cerebellar regions. The right fronto-temporal-parietal cluster including the supplementary eye field and the right basal forebrain showed stronger co-activation in subjects with higher metacognitive efficiency. Our results provide novel evidence for co-activation of widely distributed fronto-parieto-temporal regions involved in visual confidence. The supplementary eye field was the only region that activated for both decision confidence and metacognitive efficiency, suggesting the supplementary eye field plays a key role in visual metacognition. Our results link findings in electrophysiology studies and human fMRI studies and provide evidence that confidence estimates arise from the integration of multiple information processing pathways.

The temporal evolution of pre-stimulus slow cortical potentials is associated with an upcoming stimulus' access to visual consciousness.

Slow cortical potentials (SCPs) have been proposed to be essential for the formation of conscious experience. To examine their temporal characteristics, we recorded electroencephalography during a visual backward-masking task, which required participants to localize the missing part of a target stimulus. A subsequent confidence rating was used as a proxy for the target's access to consciousness. Event-related potentials (ERPs) of all correct trials were determined relative to a brief period immediately before the target and then compared among consciousness levels. In an interval ranging from 2 s prior to target presentation up to this period, a negative relationship between slowly fluctuating ERP values and the level of consciousness became evident. After target presentation, high conscious awareness was characterized by an enhanced visual awareness negativity, an increased P3 component, and associated positive SCPs. Together, these findings add new evidence to the proposed role of SCPs in the emergence of visual consciousness.

Frequency-Dependent Spatial Distribution of Functional Hubs in the Human Brain and Alterations in Major Depressive Disorder.

Alterations in large-scale brain intrinsic functional connectivity (FC), i.e., coherence between fluctuations of ongoing activity, have been implicated in major depressive disorder (MDD). Yet, little is known about the frequency-dependent alterations of FC in MDD. We calculated frequency specific degree centrality (DC) - a measure of overall FC of a brain region - within 10 distinct frequency sub-bands accessible from the full range of resting-state fMRI BOLD fluctuations (i.e., 0.01-0.25 Hz) in 24 healthy controls and 24 MDD patients. In healthy controls, results reveal a frequency-specific spatial distribution of highly connected brain regions - i.e., hubs - which play a fundamental role in information integration in the brain. MDD patients exhibited significant deviations from the healthy DC patterns, with decreased overall connectedness of widespread regions, in a frequency-specific manner. Decreased DC in MDD patients was observed predominantly in the occipital cortex at low frequencies (0.01-0.1 Hz), in the middle cingulate cortex, sensorimotor cortex, lateral parietal cortex, and the precuneus at middle frequencies (0.1-0.175 Hz), and in the anterior cingulate cortex at high frequencies (0.175-0.25 Hz). Additionally, decreased DC of distinct parts of the insula was observed across low, middle, and high frequency bands. Frequency-specific alterations in the DC of the temporal, insular, and lateral parietal cortices correlated with symptom severity. Importantly, our results indicate that frequency-resolved analysis within the full range of frequencies accessible from the BOLD signal - also including higher frequencies (>0.1 Hz) - reveals unique information about brain organization and its changes, which can otherwise be overlooked.

Altered reward-related effective connectivity in obsessive-compulsive disorder: an fMRI study

Background: Obsessive­compulsive disorder (OCD) is characterized by anxiety-provoking, obsessive thoughts. Patients usually react to these thoughts with repetitive behaviours that reduce anxiety and are perceived as rewarding. Hence, reward plays a major role in the psychopathology of OCD. Previous studies showed altered activation in frontostriatal networks, among others, in association with the processing of reward in patients with OCD. Potential alterations in connectivity within these networks have, however, barely been explored. Methods: We investigated a sample of patients with OCD and healthy controls using functional MRI and a reward learning task presented in an event-related design. Dynamic causal modelling (DCM) was used to estimate effective connectivity. Results: Our sample included 37 patients with OCD and 39 healthy controls. Analyses of task-related changes in connectivity showed a significantly altered effective connectivity between the ventromedial prefrontal cortex (vmPFC) and the orbitofrontal cortex (OFC), among others, both in terms of endogenous connectivity as well as modulatory effects under positive feedback. Clinical measures of compulsion correlated with the effect of feedback input on visual sensory areas. Limitations: The reported alterations should be interpreted within the context of the task and the a priori­defined network considered in the analysis. Conclusion: This disrupted connectivity in parts of the default mode network and the frontostriatal network may indicate increased rumination and self-related processing impairing the responsiveness toward external rewards. This, in turn, may underlie the general urge for reinforcement accompanying compulsive behaviours.

Automated quantitative evaluation of brain MRI may be more accurate for discriminating preterm born adults.

OBJECTIVE: To investigate the structural brain abnormalities and their diagnostic accuracy through qualitative and quantitative analysis in term born and very preterm birth or with very low birth weight (VP/VLBW) adults. METHODS: We analyzed 3-T MRIs acquired in 2011-2013 from 67 adults (27 term born controls, mean age 26.4 years, 8 females; 40 VP/VLBWs, mean age 26.6 years, 16 females). We compared automatic segmentations of the white matter, deep gray matter and cortical gray matter, manual corpus callosum measurements and visual ratings of the ventricles and white matter with t tests, logistic regression, and receiver operator characteristic (ROC) curves. RESULTS: Automatic segmentation correctly classified 84% of cases; visual ratings correctly classified 63%. Quantitative volumetry based on automatic segmentation revealed higher ventricular volume, lower posterior corpus callosum, and deep gray matter volumes in VP/VLBW subjects compared to controls (p < 0.01). Visual rating and manual measurement revealed a thinner corpus callosum in VP/VLBW adults (p = 0.04) and deformed lateral ventricles (p = 0.03) and tendency towards more "dirty" white matter (p = 0.06). Automatic/manual measures combined with visual ratings correctly classified 87% of cases. Stepwise logistic regression identified three independent features that correctly classify 81% of cases: ventricular volume, deep gray matter volume, and white matter aspect. CONCLUSION: Enlarged and deformed lateral ventricles, thinner corpus callosum, and "dirty" white matter are prevalent in preterm born adults. Their visual evaluation has low diagnostic accuracy. Automatic volume quantification is more accurate but time consuming. It may be useful to ask for prematurity before initiating further diagnostics in subjects with these alterations. KEY POINTS: • Our study confirms prior reports showing that structural brain abnormalities related to preterm birth persist into adulthood. • In the clinical practice, if large and deformed lateral ventricles, small and thin corpus callosum, and "dirty" white matter are visible on MRI, ask for prematurity before considering other diagnoses. • Although prevalent, visual findings have low accuracy; adding automatic segmentation of lateral ventricles and deep gray matter nuclei improves the diagnostic accuracy.

Specific Substantial Dysconnectivity in Schizophrenia: A Transdiagnostic Multimodal Meta-analysis of Resting-State Functional and Structural Magnetic Resonance Imaging Studies.

BACKGROUND: This study investigated characteristic large-scale brain changes in schizophrenia. Numerous imaging studies have demonstrated brain changes in schizophrenia, particularly aberrant intrinsic functional connectivity (iFC) of ongoing brain activity, measured by resting-state functional magnetic resonance imaging, and aberrant gray matter volume (GMV) of distributed brain regions, measured by structural magnetic resonance imaging. It is unclear, however, which iFC changes are specific to schizophrenia compared with those of other disorders and whether such specific iFC changes converge with GMV changes. To address this question of specific substantial dysconnectivity in schizophrenia, we performed a transdiagnostic multimodal meta-analysis of resting-state functional and structural magnetic resonance imaging studies in schizophrenia and other psychiatric disorders. METHODS: Multiple databases were searched up to June 2017 for whole-brain seed-based iFC studies and voxel-based morphometry studies in schizophrenia, major depressive disorder, bipolar disorder, addiction, and anxiety. Coordinate-based meta-analyses were performed to detect 1) schizophrenia-specific hyperconnectivity or hypoconnectivity of intrinsic brain networks (compared with hyperconnectivity or hypoconnectivity of each other disorder both separately and combined across comparisons) and 2) the overlap between dysconnectivity and GMV changes (via multimodal conjunction analysis). RESULTS: For iFC meta-analysis, 173 publications comprising 4962 patients and 4575 control subjects were included, and for GMV meta-analysis, 127 publications comprising 6311 patients and 6745 control subjects were included. Disorder-specific iFC dysconnectivity in schizophrenia (consistent across comparisons with other disorders) was found for limbic, frontoparietal executive, default mode, and salience networks. Disorder-specific dysconnectivity and GMV reductions converged in insula, lateral postcentral cortex, striatum, and thalamus. CONCLUSIONS: Results demonstrated specific substantial dysconnectivity in schizophrenia in insula, lateral postcentral cortex, striatum, and thalamus. Data suggest that these regions are characteristic targets of schizophrenia.

Grading of Frequency Spectral Centroid Across Resting-State Networks.

Ongoing, slowly fluctuating brain activity is organized in resting-state networks (RSNs) of spatially coherent fluctuations. Beyond spatial coherence, RSN activity is governed in a frequency-specific manner. The more detailed architecture of frequency spectra across RSNs is, however, poorly understood. Here we propose a novel measure-the Spectral Centroid (SC)-which represents the center of gravity of the full power spectrum of RSN signal fluctuations. We examine whether spectral underpinnings of network fluctuations are distinct across RSNs. We hypothesize that spectral content differs across networks in a consistent way, thus, the aggregate representation-SC-systematically differs across RSNs. We therefore test for a significant grading (i.e., ordering) of SC across RSNs in healthy subjects. Moreover, we hypothesize that such grading is biologically significant by demonstrating its RSN-specific change through brain disease, namely major depressive disorder. Our results yield a highly organized grading of SC across RSNs in 820 healthy subjects. This ordering was largely replicated in an independent dataset of 25 healthy subjects, pointing toward the validity and consistency of found SC grading across RSNs. Furthermore, we demonstrated the biological relevance of SC grading, as the SC of the salience network-a RSN well known to be implicated in depression-was specifically increased in patients compared to healthy controls. In summary, results provide evidence for a distinct grading of spectra across RSNs, which is sensitive to major depression.

Fronto-Insular Connectivity during Pain Distraction Is Impaired in Patients with Somatoform Pain.

BACKGROUND AND PURPOSE: Somatoform pain disorder is characterized by chronic pain and various psychological symptoms including increased attention to mental and physical processes. Given that the medial prefrontal cortex (mPFC) of the default mode network (DMN) and the anterior insula of the salience network are critically involved in intrinsic and attentional processes, we investigated the involvement of these networks during the distraction from physical pain in somatoform pain patients. METHODS: During painful and nonpainful heat stimulation, attentional distraction from physical processes was modulated with a Stroop task. Thirteen patients were investigated with functional magnetic resonance imaging (fMRI) and compared to 13 controls. Main outcomes were spatial maps of coherent fMRI activity based on independent component analysis and functional connectivity (FC) resulting from psychophysiological interaction analysis. RESULTS: Behavioral pain intensity ratings were reduced during the distraction task in both groups. At brain level, we found deviant network activities in the DMN (particularly in the mPFC) and in the salience network (bilaterally in the anterior insula) in patients. During pain stimulation, Stroop-induced distraction decreased the FC between the mPFC and anterior insula in controls but not in patients. CONCLUSIONS: Modulating the FC between the mPFC and the insula may be highly relevant for shifting the attention away from external stimuli, including nociceptive input. The observed alterations in somatoform pain patients may foster new strategies in cognitive behavioral training tools for these patients.

Spectral Dynamics of Resting State fMRI Within the Ventral Tegmental Area and Dorsal Raphe Nuclei in Medication-Free Major Depressive Disorder in Young Adults.

Background: Dorsal raphe nucleus (DRN) and ventral tegmental area (VTA) are major brainstem monamine nuclei consisting of serotonin and dopamine neurons respectively. Animal studies show that firing patterns in both nuclei are altered when animals exhibit depression like behaviors. Functional MRI studies in humans have shown reduced VTA activation and DRN connectivity in depression. This study for the first time aims at investigating the functional integrity of local neuronal firing concurrently in both the VTA and DRN in vivo in humans using spectral analysis of resting state low frequency fluctuation fMRI. Method: A total of 97 medication-free subjects-67 medication-free young patients (ages 18-30) with major depressive disorder and 30 closely matched healthy controls were included in the study to detect aberrant dynamics in DRN and VTA. For the investigation of altered localized dynamics we conducted power spectral analysis and above this spectral cross correlation between the two groups. Complementary to this, spectral dependence of permutation entropy, an information theoretical measure, was compared between groups. Results: Patients displayed significant spectral slowing in VTA vs. controls (p = 0.035, corrected). In DRN, spectral slowing was less pronounced, but the amount of slowing significantly correlated with 17-item Hamilton Depression Rating scores of depression severity (p = 0.038). Signal complexity as assessed via permutation entropy showed spectral alterations inline with the results on spectral slowing. Conclusion: Our results indicate that altered functional dynamics of VTA and DRN in depression can be detected from regional fMRI signal. On this basis, impact of antidepressant treatment and treatment response can be assessed using these markers in future studies.

Common and distinct changes of default mode and salience network in schizophrenia and major depression.

Brain imaging reveals schizophrenia as a disorder of macroscopic brain networks. In particular, default mode and salience network (DMN, SN) show highly consistent alterations in both interacting brain activity and underlying brain structure. However, the same networks are also altered in major depression. This overlap in network alterations induces the question whether DMN and SN changes are different across both disorders, potentially indicating distinct underlying pathophysiological mechanisms. To address this question, we acquired T1-weighted, diffusion-weighted, and resting-state functional MRI in patients with schizophrenia, patients with major depression, and healthy controls. We measured regional gray matter volume, inter-regional structural and intrinsic functional connectivity of DMN and SN, and compared these measures across groups by generalized Wilcoxon rank tests, while controlling for symptoms and medication. When comparing patients with controls, we found in each patient group SN volume loss, impaired DMN structural connectivity, and aberrant DMN and SN functional connectivity. When comparing patient groups, SN gray matter volume loss and DMN structural connectivity reduction did not differ between groups, but in schizophrenic patients, functional hyperconnectivity between DMN and SN was less in comparison to depressed patients. Results provide evidence for distinct functional hyperconnectivity between DMN and SN in schizophrenia and major depression, while structural changes in DMN and SN were similar. Distinct hyperconnectivity suggests different pathophysiological mechanism underlying aberrant DMN-SN interactions in schizophrenia and depression.

Increased Global Interaction Across Functional Brain Modules During Cognitive Emotion Regulation.

Cognitive emotion regulation (CER) enables humans to flexibly modulate their emotions. While local theories of CER neurobiology suggest interactions between specialized local brain circuits underlying CER, e.g., in subparts of amygdala and medial prefrontal cortices (mPFC), global theories hypothesize global interaction increases among larger functional brain modules comprising local circuits. We tested the global CER hypothesis using graph-based whole-brain network analysis of functional MRI data during aversive emotional processing with and without CER. During CER, global between-module interaction across stable functional network modules increased. Global interaction increase was particularly driven by subregions of amygdala and cuneus-nodes of highest nodal participation-that overlapped with CER-specific local activations, and by mPFC and posterior cingulate as relevant connector hubs. Results provide evidence for the global nature of human CER, complementing functional specialization of embedded local brain circuits during successful CER.

Impaired visual short-term memory capacity is distinctively associated with structural connectivity of the posterior thalamic radiation and the splenium of the corpus callosum in preterm-born adults.

Preterm birth is associated with an increased risk for lasting changes in both the cortico-thalamic system and attention; however, the link between cortico-thalamic and attention changes is as yet little understood. In preterm newborns, cortico-cortical and cortico-thalamic structural connectivity are distinctively altered, with increased local clustering for cortico-cortical and decreased integrity for cortico-thalamic connectivity. In preterm-born adults, among the various attention functions, visual short-term memory (vSTM) capacity is selectively impaired. We hypothesized distinct associations between vSTM capacity and the structural integrity of cortico-thalamic and cortico-cortical connections, respectively, in preterm-born adults. A whole-report paradigm of briefly presented letter arrays based on the computationally formalized Theory of Visual Attention (TVA) was used to quantify parameter vSTM capacity in 26 preterm- and 21 full-term-born adults. Fractional anisotropy (FA) of posterior thalamic radiations and the splenium of the corpus callosum obtained by diffusion tensor imaging were analyzed by tract-based spatial statistics and used as proxies for cortico-thalamic and cortico-cortical structural connectivity. The relationship between vSTM capacity and cortico-thalamic and cortico-cortical connectivity, respectively, was significantly modified by prematurity. In full-term-born adults, the higher FA in the right posterior thalamic radiation the higher vSTM capacity; in preterm-born adults this FA-vSTM-relationship was inversed. In the splenium, higher FA was correlated with higher vSTM capacity in preterm-born adults, whereas no significant relationship was evident in full-term-born adults. These results indicate distinct associations between cortico-thalamic and cortico-cortical integrity and vSTM capacity in preterm-and full-term-born adults. Data suggest compensatory cortico-cortical fiber re-organization for attention deficits after preterm delivery.

Reduced Cholinergic Basal Forebrain Integrity Links Neonatal Complications and Adult Cognitive Deficits After Premature Birth.

BACKGROUND: Prematurely born individuals have an increased risk for long-term neurocognitive impairments. In animal models, development of the cholinergic basal forebrain (cBF) is selectively vulnerable to adverse effects of perinatal stressors, and impaired cBF integrity results in lasting cognitive deficits. We hypothesized that cBF integrity is impaired in prematurely born individuals and mediates adult cognitive impairments associated with prematurity. METHODS: We used magnetic resonance imaging-based volumetric assessments of a cytoarchitectonically defined cBF region of interest to determine differences in cBF integrity between 99 adults who were born very preterm and/or with very low birth weight and 106 term-born control subjects from the same birth cohort. Magnetic resonance imaging-derived cBF volumes were studied in relation to neonatal clinical complications after delivery and intelligence measures (IQ) in adulthood. RESULTS: In adults who were born very preterm and/or with very low birth weight, cBF volumes were significantly reduced compared with term-born adults (-4.5% [F1,202 = 11.82, p = .001]). Lower cBF volume in adults who were born very preterm and/or with very low birth weight was specifically associated with both neonatal complications (rpart,92 = -.35, p < .001) and adult IQ (rpart,88 = .33, p = .001) even after controlling for global gray matter and white matter volume. In a path analytic model, cBF volume significantly mediated the association between neonatal complications and adult cognitive deficits. CONCLUSIONS: We provide first-time evidence in humans that cBF integrity is impaired after premature birth and links neonatal complications with long-term cognitive outcome. Data suggest that cholinergic system abnormalities may play a relevant role for long-term neurocognitive impairments associated with premature delivery.

Cognitive emotion regulation modulates the balance of competing influences on ventral striatal aversive prediction error signals.

Cognitive emotion regulation (CER) is a critical human ability to face aversive emotional stimuli in a flexible way, via recruitment of specific prefrontal brain circuits. Animal research reveals a central role of ventral striatum in emotional behavior, for both aversive conditioning, with striatum signaling aversive prediction errors (aPE), and for integrating competing influences of distinct striatal inputs from regions such as the prefrontal cortex (PFC), amygdala, hippocampus and ventral tegmental area (VTA). Translating these ventral striatal findings from animal research to human CER, we hypothesized that successful CER would affect the balance of competing influences of striatal afferents on striatal aPE signals, in a way favoring PFC as opposed to 'subcortical' (i.e., non-isocortical) striatal inputs. Using aversive Pavlovian conditioning with and without CER during fMRI, we found that during CER, superior regulators indeed reduced the modulatory impact of 'subcortical' striatal afferents (hippocampus, amygdala and VTA) on ventral striatal aPE signals, while keeping the PFC impact intact. In contrast, inferior regulators showed an opposite pattern. Our results demonstrate that ventral striatal aPE signals and associated competing modulatory inputs are critical mechanisms underlying successful cognitive regulation of aversive emotions in humans.

Progressively Disrupted Intrinsic Functional Connectivity of Basolateral Amygdala in Very Early Alzheimer's Disease.

Very early Alzheimer's disease (AD) - i.e., AD at stages of mild cognitive impairment (MCI) and mild dementia - is characterized by progressive structural and neuropathologic changes, such as atrophy or tangle deposition in medial temporal lobes, including hippocampus and entorhinal cortex and also adjacent amygdala. While progressively disrupted intrinsic connectivity of hippocampus with other brain areas has been demonstrated by many studies, amygdala connectivity was rarely investigated in AD, notwithstanding its known relevance for emotion processing and mood disturbances, which are both important in early AD. Intrinsic functional connectivity (iFC) patterns of hippocampus and amygdala overlap in healthy persons. Thus, we hypothesized that increased alteration of iFC patterns along AD is not limited to the hippocampus but also concerns the amygdala, independent from atrophy. To address this hypothesis, we applied structural and functional resting-state MRI in healthy controls (CON, n = 33) and patients with AD in the stages of MCI (AD-MCI, n = 38) and mild dementia (AD-D, n = 36). Outcome measures were voxel-based morphometry (VBM) values and region-of-interest-based iFC maps of basolateral amygdala, which has extended cortical connectivity. Amygdala VBM values were progressively reduced in patients (CON > AD-MCI and AD-D). Amygdala iFC was progressively reduced along impairment severity (CON > AD-MCI > AD-D), particularly for hippocampus, temporal lobes, and fronto-parietal areas. Notably, decreased iFC was independent of amygdala atrophy. Results demonstrate progressively impaired amygdala intrinsic connectivity in temporal and fronto-parietal lobes independent from increasing amygdala atrophy in very early AD. Data suggest that early AD disrupts intrinsic connectivity of medial temporal lobe key regions, including that of amygdala.

Ongoing Slow Fluctuations in V1 Impact on Visual Perception.

The human brain's ongoing activity is characterized by intrinsic networks of coherent fluctuations, measured for example with correlated functional magnetic resonance imaging signals. So far, however, the brain processes underlying this ongoing blood oxygenation level dependent (BOLD) signal orchestration and their direct relevance for human behavior are not sufficiently understood. In this study, we address the question of whether and how ongoing BOLD activity within intrinsic occipital networks impacts on conscious visual perception. To this end, backwardly masked targets were presented in participants' left visual field only, leaving the ipsi-lateral occipital areas entirely free from direct effects of task throughout the experiment. Signal time courses of ipsi-lateral BOLD fluctuations in visual areas V1 and V2 were then used as proxies for the ongoing contra-lateral BOLD activity within the bilateral networks. Magnitude and phase of these fluctuations were compared in trials with and without conscious visual perception, operationalized by means of subjective confidence ratings. Our results show that ipsi-lateral BOLD magnitudes in V1 were significantly higher at times of peak response when the target was perceived consciously. A significant difference between conscious and non-conscious perception with regard to the pre-target phase of an intrinsic-frequency regime suggests that ongoing V1 fluctuations exert a decisive impact on the access to consciousness already before stimulation. Both effects were absent in V2. These results thus support the notion that ongoing slow BOLD activity within intrinsic networks covering V1 represents localized processes that modulate the degree of readiness for the emergence of visual consciousness.