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Background Several fMRI studies found hyperactivity in the hippocampus during pattern separation tasks in patients with Mild Cognitive Impairment (MCI; a prodromal stage of Alzheimer’s disease). This was associated with memory deficits, subsequent cognitive decline, and faster clinical progression. A reduction of hippocampal hyperactivity with an antiepileptic drug improved memory performance. Pharmacological interventions, however, entail the risk of side effects. An alternative approach may be real-time fMRI neurofeedback, during which individuals learn to control region-specific brain activity. In the current project we aim to test the potential of neurofeedback to reduce hippocampal hyperactivity and thereby improve memory performance. Methods In a single-blind parallel-group study, we will randomize n = 84 individuals (n = 42 patients with MCI, n = 42 healthy elderly volunteers) to one of two groups receiving feedback from either the hippocampus or a functionally independent region. Percent signal change of the hemodynamic response within the respective target region will be displayed to the participant with a thermometer icon. We hypothesize that only feedback from the hippocampus will decrease hippocampal hyperactivity during pattern separation and thereby improve memory performance. Discussion Results of this study will reveal whether real-time fMRI neurofeedback is able to reduce hippocampal hyperactivity and thereby improve memory performance. In addition, the results of this study may identify predictors of successful neurofeedback as well as the most successful regulation strategies. Trial registration The study has been registered with clinicaltrials.gov on the 16th of July 2019 (trial identifier: NCT04020744).

Pain habituation is associated with a decrease of activation in brain areas related to pain perception. However, little is known about the specificity of these decreases to pain, as habituation has also been described for other responses like spinal reflexes and other sensory responses. Thus, it might be hypothesized that previously reported reductions in activation are not specifically related to pain habituation. For this reason, we performed a 3 T fMRI study using either painful or non-painful electrical stimulation via an electrode attached to the back of the left hand. Contrasting painful vs. non-painful stimulation revealed significant activation clusters in regions well-known to be related to pain processing, such as bilateral anterior and posterior insula, primary/secondary sensory cortices (S1/S2) and anterior midcingulate cortex (aMCC). Importantly, our results show distinct habituation patterns for painful (in aMCC) and non-painful (contralateral claustrum) stimulation, while similar habituation for both types of stimulation was identified in bilateral inferior frontal gyrus (IFG) and contralateral S2. Our findings thus distinguish a general habituation in somatosensory processing (S2) and reduced attention (IFG) from specific pain and non-pain related habituation effects where pain-specific habituation effects within the aMCC highlight a change in affective pain perception.

Cooperation and mutual trust are essential in our society, yet not everybody is trustworthy. In this fMRI study, 62 healthy volunteers performed a repeated trust game, placing trust in a trustworthy or an untrustworthy player. We found that the central amygdala was active during trust behavior planning while the basolateral amygdala was active during outcome evaluation. When planning the trust behavior, central and basolateral amygdala activation was stronger for the untrustworthy player compared to the trustworthy player but only in participants who actually learned to differentiate the trustworthiness of the players. Independent of learning success, nucleus accumbens encoded whether trust was reciprocated. This suggests that learning whom to trust is not related to reward processing in the nucleus accumbens, but rather to engagement of the amygdala. Our study overcomes major empirical gaps between animal models and human neuroimaging and shows how different subnuclei of the amygdala and connected areas orchestrate learning to form different subjective trustworthiness beliefs about others and guide trust choice behavior., Sladky & Riva et al. investigated how human allocation of trust depends on brain activity of the amygdala, a core brain structure for social cognition. They found dissociated activation between the amygdala and the nucleus accumbens, the former coding for trust assignation, and the latter coding for trust reciprocation.

INTRODUCTION The importance of the amygdala - medial orbitofrontal cortex (OFC) network during processing of emotional stimuli, emotional faces in particular, is well established. This premise is supported by converging evidence from animal models, human neuroanatomical results, and neuroimaging studies. However, there is missing evidence from human brain connectivity studies that the OFC and no other prefrontal brain areas such as the DLPFC or VLPFC are responsible for amygdala regulation in the functional context of emotional face stimuli. METHODS Dynamic causal modeling of ultra-high field functional MRI data acquired at 7 Tesla in 38 healthy subjects and a well-established paradigm for emotional face processing were used to assess the central role of the OFC in order to provide empirical validation for the assumed network architecture. RESULTS Using Bayesian model selection, it is demonstrated that indeed the OFC, and not the VLPFC and the DLPFC, down regulates amygdala activation during the emotion discrimination task. Additionally, Bayesian model averaging group results were rigorously tested using bootstrapping, further corroborating these findings and providing an estimator for robustness and optimal sample sizes. DISCUSSION While it is true that VLPFC and DLPFC are relevant for the processing of emotional faces and are connected to the OFC, the OFC appears to be a central hub for prefrontal-amygdala interaction.

The aim of this study was to investigate the effect of acute dopamine agonistic and antagonistic manipulation on the visual-cue induced blood oxygen level-dependent signal response in healthy volunteers. Seventeen healthy volunteers in a double-blind placebo-controlled cross-over design received either a dopamine antagonist, agonist or placebo and underwent functional magnetic resonance imaging. Using classical inference and Bayesian statistics, we found no effect of dopaminergic modulation on properties of visual-cue induced blood oxygen level-dependent signals in the visual cortex, particularly on distinct properties of the haemodynamic response function (amplitude, time-to-peak and width). Dopamine-related effects modulating the neurovascular coupling in the visual cortex might be negligible when measured via functional magnetic resonance imaging.

Creativity is a sine qua non ability for almost all aspects of everyday life. Although very profound behavioural models were provided by 21st century psychologists, the neural correlates of these personality features associated with creativity are largely unknown. Recent models suggest strong relationships between dopamine release and various creative skills. Herein, we employed functional connectivity analyses of resting-state functional magnetic imaging data in order to shed light on these neural underpinnings of creative aspects. For improved sensitivity, we performed the study at ultra-high magnetic field (7 T). Seed regions were defined based on subcortical (ventral tegmental area/substantia nigra, nucleus caudatus) activation foci of a remote associates task (RAT). In addition, bilateral PCC was used as seed region to examine the default-mode network. Network strength across subjects was regressed against a battery of psychological variables related to creativity. Dopaminergic network variations turned out to be indicative for individual differences in creative traits. In this regard, the caudate network showed stronger connectivity in individuals with higher extraversion measures, while connectivity with the midbrain network was found increased with higher ideational behaviour and emotional stability.

Human societies are built on cooperation and mutual trust, but not everybody is trustworthy. Research on rodents suggests an essential role of the basolateral amygdala (BLA) in learning from social experiences (Hernandez-Lallement J et al., 2016), which was also confirmed in human subjects with selective bilateral BLA damage as they failed to adapt their trust behavior towards trustworthy vs. untrustworthy interaction partners (Rosenberger LA et al., 2019). However, neuroimaging in neurotypical populations did not consistently report involvement of the amygdala in trust behavior. This might be explained by the difficulty of differentiating between amygdala’s structurally and functionally different subnuclei, i.e., the BLA and central amygdala (CeA), which have even antagonistic features particularly in trust behavior (van Honk J et al., 2013). Here, we used fMRI of the amygdala subnuclei of neurotypical adults (n=31f/31m) engaging in the repeated trust game. Our data show that both the BLA and the CeA play a role and indeed differentially: While the BLA was most active when obtaining feedback on whether invested trust had been reciprocated or not, the CeA was most active when subjects were preparing their next trust decision. In the latter phase, improved learning was associated with higher activation differences in response to untrustworthy vs. trustworthy trustees, in both BLA and CeA. Our data not only translate to rodent models and support our earlier findings in BLA-damaged subjects, but also show the specific contributions of other brain structures in the amygdala-centered network in learning whom to trust, and better not to trust.SIGNIFICANCE STATEMENTIn this fMRI study, the central amygdala was found active during trust behavior planning, while the basolateral amygdala was active during outcome evaluation. When planning trust behavior, central and basolateral amygdala activation differences between the players was related to whether participants learned to differentiate the players’ trustworthiness. Nucleus accumbens tracked whether trust was reciprocated but was not related to learning. This suggests learning whom to trust is not related to reward processing in the nucleus accumbens but rather to engagement of the basolateral amygdala. This study overcomes major empirical gaps between animal models and human neuroimaging and shows how different amygdala subnuclei and connected areas orchestrate learning to form different subjective trustworthiness beliefs about others and guide trust choice behavior.

Tobacco smoking is one of the leading causes of preventable death and disease worldwide. Most smokers want to quit, but relapse rates are high. To improve current smoking cessation treatments, a better understanding of the underlying mechanisms of nicotine dependence and related craving behaviour is needed. Studies on cue-driven cigarette craving have been a particularly useful tool for investigating the neural mechanisms of drug craving. Here, functional neuroimaging studies in humans have identified a core network of craving-related brain responses to smoking cues that comprises of amygdala, anterior cingulate cortex, orbitofrontal cortex, posterior cingulate cortex and ventral striatum. However, most functional Magnetic Resonance Imaging (fMRI) cue-reactivity studies do not adjust their stimuli for emotional valence, a factor assumed to confound craving-related brain responses to smoking cues. Here, we investigated the influence of emotional valence on key addiction brain areas by disentangling craving- and valence-related brain responses with parametric modulators in 32 smokers. For one of the suggested key regions for addiction, the amygdala, we observed significantly stronger brain responses to the valence aspect of the presented images than to the craving aspect. Our results emphasize the need for carefully selecting stimulus material for cue-reactivity paradigms, in particular with respect to emotional valence. Further, they can help designing future research on teasing apart the diverse psychological dimensions that comprise nicotine dependence and, therefore, can lead to a more precise mapping of craving-associated brain areas, an important step towards more tailored smoking cessation treatments.

Tobacco smoking is one of the leading causes of preventable death and disease worldwide. Most smokers want to quit, but relapse rates are high. To improve current smoking cessation treatments, a better understanding of the underlying mechanisms of nicotine dependence and related craving behavior is needed. Studies on cue-driven cigarette craving have been a particularly useful tool for investigating the neural mechanisms of drug craving. Here, functional neuroimaging studies in humans have identified a core network of craving-related brain responses to smoking cues that comprises of amygdala, anterior cingulate cortex, orbitofrontal cortex, posterior cingulate cortex, and ventral striatum.However, most functional Magnetic Resonance Imaging (fMRI) cue-reactivity studies do not adjust their stimuli for emotional valence, a factor assumed to confound craving-driven brain responses to smoking cues. Here, we investigated the influence of emotional valence on key addiction brain areas by disentangling craving- and valence-related brain responses with parametric modulators in 32 smokers. For one of the suggested key regions for addiction, the amygdala, we observed significantly stronger brain responses to the valence aspect of the presented images than to the craving aspect. Our results emphasize the need for carefully selecting stimulus material for cue-reactivity paradigms, in particular with respect to emotional valence. Further, they can help designing future research on teasing apart the diverse psychological dimensions that comprise nicotine dependence, and, therefore, can lead to a more precise mapping of craving-associated brain areas, an important step towards more tailored smoking cessation treatments.

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large interindividual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pre-training functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pre-training activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real‐time fMRI neurofeedback studies report large inter‐individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta‐analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no‐feedback runs (i.e., self‐regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain‐based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning., Many real‐time fMRI neurofeedback studies report large inter‐individual differences in learning success, but the factors that cause this vast variability between participants remain unknown. Here, we used a meta‐analytic approach including data from 24 different neurofeedback studies with a total of 401 participants to determine whether levels of activity in target brain regions during pretraining functional localizer or no‐feedback runs could predict neurofeedback learning success. We were not able to identify common brain‐based success predictors across our diverse cohort of studies.

Finding creative solutions to difficult problems is a fundamental aspect of human culture and a skill highly needed. However, the exact neural processes underlying creative problem solving remain unclear. Insightful problem solving tasks were shown to be a valid method for investigating one subcomponent of creativity: the Aha!‐moment. Finding insightful solutions during a remote associates task (RAT) was found to elicit specific cortical activity changes. Considering the strong affective components of Aha!‐moments, as manifested in the subjectively experienced feeling of relief following the sudden emergence of the solution of the problem without any conscious forewarning, we hypothesized the subcortical dopaminergic reward network to be critically engaged during Aha. To investigate those subcortical contributions to insight, we employed ultra‐high‐field 7 T fMRI during a German Version of the RAT. During this task, subjects were exposed to word triplets and instructed to find a solution word being associated with all the three given words. They were supposed to press a button as soon as they felt confident about their solution without further revision, allowing us to capture the exact event of Aha!‐moment. Besides the finding on cortical involvement of the left anterior middle temporal gyrus (aMTG), here we showed for the first time robust subcortical activity changes related to insightful problem solving in the bilateral thalamus, hippocampus, and the dopaminergic midbrain comprising ventral tegmental area (VTA), nucleus accumbens (NAcc), and caudate nucleus. These results shed new light on the affective neural mechanisms underlying insightful problem solving.

Background: Cue-reactivity paradigms provide valuable insights into the underlying mechanisms of nicotine craving in nicotine-dependent subjects. In order to study cue-driven nicotine craving, robust and validated stimulus datasets are essential. Objectives: The aim of this study was to generate and validate a large set of individually rated smoking-related cues that allow for assessment of different stimulus intensities along the dimensions craving, valence, and arousal. Methods: The image database consisted of 330 visual cues. Two hundred fifty smoking-associated pictures (Creative Commons license) were chosen from online databases and showed a widespread variety of smoking-associated content. Eighty pictures from previously published databases were included for cross-validation. Forty volunteers with tobacco use disorder rated “urge-to-smoke,” “valence,” and “arousal” for all images on a 100-point visual analogue scale. Pictures were also labelled according to 18 categories such as lit/unlit cigarettes in mouth, cigarette end, and cigarette in ashtray. Results: Ratings (mean ± SD) were as follows: urge to smoke, 44.9 ± 13.2; valence, 51.2 ± 7.6; and arousal, 54.6 ± 7.1. All ratings, particularly “urge to smoke,” were widely distributed along the whole scale spectrum. Conclusions: We present a novel image library of well-described smoking-related cues, which were rated on a continuous scale along the dimensions craving, valence, and arousal that accounts for inter-individual differences. The rating software, image database, and their ratings are publicly available at https://smocuda.github.io.

Major depressive disorder (MDD) has been hypothesized to lead to impairments in empathy. Previous cross-sectional studies did not disentangle effects of MDD itself and antidepressant treatment. In this first longitudinal neuroimaging study on empathy in depression, 29 patients with MDD participated in two functional magnetic resonance imaging (fMRI) sessions before and after 3 months of antidepressant therapy. We compared their responses to an empathy for pain task to a group of healthy controls (N = 35). All participants provided self-report ratings targeting cognitive (perspective taking) and affective (unpleasant affect) aspects of empathy. To control for general effects on processing of negative affective states, participants additionally underwent an electrical pain task. Before treatment, we found no differences in empathic responses between controls and patients with MDD. After treatment, patients showed significant decreases in both affective empathy and activity of three a priori selected brain regions associated with empathy for pain. Decreases in affective empathy were moreover correlated with symptom improvement. Moreover, functional connectivity during the empathy task between areas associated with affective (anterior insula) and cognitive (precuneus) empathy decreased between sessions in the MDD group. Neither cognitive empathy nor responses to painful electrical shocks were changed after treatment. These findings contradict previous cross-sectional reports of empathy deficits in acute MDD. Rather, they suggest that antidepressant treatment reduces the aversive responses triggered by exposure to the suffering of others. Importantly, this cannot be explained by a general blunting of negative affect, as treatment did not change self-experienced pain.

Sex-steroid hormones are primarily involved in sexual differentiation and development and are thought to underlie processes related to cognition and emotion. However, divergent results have been reported concerning the effects of hormone administration on brain structure including side effects like brain atrophy and dementia. Cross-sex hormone therapy in transgender subjects offers a unique model for studying the effects of sex hormones on the living human brain. In this study, 25 Female-to-Male (FtM) and 14 Male-to-Female (MtF) subjects underwent MRI examinations at baseline and after a period of at least 4-months of continuous cross-sex hormone administration. While MtFs received estradiol and anti-androgens, FtM subjects underwent high-dose testosterone treatment. The longitudinal processing stream of the FreeSurfer software suite was used for the automated assessment and delineation of brain volumes to assess the structural changes over the treatment period of cross-sex hormone administration. Most prominent results were found for MtFs receiving estradiol and anti-androgens in the form of significant decreases in the hippocampal region. Further analysis revealed that these decreases were reflected by increases in the ventricles. Additionally, changes in progesterone levels correlated with changes in gray matter structures in MtF subjects. In line with prior studies, our results indicate hormonal influences on subcortical structures related to memory and emotional processing. Additionally, this study adds valuable knowledge that progesterone may play an important role in this process.

Despite its importance as the prime method for non-invasive assessment of human brain function, functional MRI (fMRI) was repeatedly challenged with regards to the validity of the fMRI-derived brain activation maps. Amygdala fMRI was particularly targeted, as the amygdala’s anatomical position in the ventral brain combined with strong magnetic field inhomogeneities and proximity to large vessels pose considerable obstacles for robust activation mapping. In this high-resolution study performed at ultra-high field (7T) fMRI, we aimed at (1) investigating systematic replicability of amygdala group-level activation in response to an established emotion processing task by varying task instruction and acquisition parameters and (2) testing for intra- and intersession reliability. At group-level, our results show statistically significant activation in bilateral amygdala and fusiform gyrus for each of the runs acquired. In addition, while fusiform gyrus activations are consistent across runs and sessions, amygdala activation levels show habituation effects across runs. This amygdala habituation effect is replicated in a session repeated two weeks later. Varying task instruction between matching emotions and matching persons does not change amygdala activation strength. Also, comparing two acquisition protocols with repetition times of either 700 ​ms or 1400 ​ms did not result in statistically significant differences of activation levels. Regarding within-subject reliability of amygdala activation, despite considerable variance in individual habituation patterns, we report fair to good inter-session reliability for the first run and excellent reliability for averages over runs. We conclude that high-resolution fMRI at 7T allows for robust mapping of amygdala activation in a broad range of variations. Our results of amygdala 7T fMRI are suitable to inform methodology and may encourage future studies to continue using emotion discrimination paradigms in clinical and non-clinical applications.

Background: Enhanced drug-related reward sensitivity accompanied by impaired sensitivity to non-drug related rewards in the mesolimbic dopamine system are thought to underlie the broad motivational deficits and dysfunctional decision-making frequently observed in cocaine use disorder (CUD). Effective approaches to modify this imbalance and reinstate non-drug reward responsiveness are urgently needed. Here we examine whether cocaine users (CU) can use mental imagery of non-drug rewards to self-regulate the ventral tegmental area and substantia nigra (VTA/SN). We expected that compulsive and obsessive thoughts about cocaine consumption would hamper the ability to self-regulate the VTA/SN. Finally, we tested if self-regulation of the VTA/SN can be improved with real-time fMRI (rtfMRI) neurofeedback (NFB).Methods: Twenty-two CU and 28 healthy controls (HC) were asked to voluntarily up-regulate VTA/SN activity with rewarding non-drug imagery alone, or combined with rtfMRI NFB of VTA/SN activity. Obsessive-compulsive drug use was measured with the Obsessive Compulsive Cocaine Use Scale (OCCUS).Results: CU were able to induce activity in the dopaminergic midbrain and other reward regions with reward imagery. The ability to self-regulate the VTA/SN was reduced in those with more severe obsessive-compulsive drug use. NFB enhanced the effect of non-drug imagery.Conclusion: CU can voluntary activate their reward system through non-drug related imagery and improve this ability with rtfMRI NFB. Combining reward imagery and rtFMRI NFB has great potential for modifying the maladapted reward sensitivity and reinstating non-drug reward responsiveness. This motivates further work to examine the therapeutic potential of cognitive neurostimulation in CUD.

Recent technological progress enables MRI recordings at ultra-high fields of 7 T and above leading to brain images of higher resolution and increased signal-to-noise ratio. Despite these benefits, imaging at 7 T exhibits distinct challenges due to B1 field inhomogeneities, causing decreased image quality and problems in data analysis. Although several strategies have been proposed, a systematic investigation of bias-corrected 7 T data for voxel-based morphometry (VBM) is still missing and it is an ongoing matter of debate if VBM at 7 T can be carried out properly. Here, an optimized VBM study was conducted, evaluating the impact of field strength (3T vs. 7 T) and pulse sequence (MPRAGE vs. MP2RAGE) on gray matter volume (GMV) estimates. More specifically, twenty-two participants were measured under the conditions 3T MPRAGE, 7 T MPRAGE and 7 T MP2RAGE. Due to the fact that 7 T MPRAGE data exhibited strong intensity inhomogeneities, an alternative preprocessing pipeline was proposed and applied for that data. VBM analysis revealed higher GMV estimates for 7 T predominantly in superior cortical areas, caudate nucleus, cingulate cortex and the hippocampus. On the other hand, 3T yielded higher estimates especially in inferior cortical areas of the brain, cerebellum, thalamus and putamen compared to 7 T. Besides minor exceptions, these results were observed for 7 T MPRAGE as well for the 7 T MP2RAGE measurements. Results gained in the inferior parts of the brain should be taken with caution, as native GM segmentations displayed misclassifications in these regions for both 7 T sequences. This was supported by the test-retest measurements showing highest variability in these inferior regions of the brain for 7 T and also for the advanced MP2RAGE sequence. Hence, our data support the use of 7 T MRI for VBM analysis in cortical areas, but direct comparison between field strengths and sequences requires careful assessment. Similarly, analysis of the inferior cortical regions, cerebellum and subcortical regions still remains challenging at 7 T even if the advanced MP2RAGE sequence is used.

Citalopram and Escitalopram are gold standard pharmaceutical treatment options for affective, anxiety, and other psychiatric disorders. However, their neurophysiologic function on cortico-limbic circuits is incompletely characterized. Here we studied the neuropharmacological influence of Citalopram and Escitalopram on cortico-limbic regulatory processes by assessing the effective connectivity between orbitofrontal cortex (OFC) and amygdala using dynamic causal modeling (DCM) applied to functional MRI data. We investigated a cohort of 15 healthy subjects in a randomized, crossover, double-blind design after 10days of Escitalopram (10mg/d (S)-citalopram), Citalopram (10mg/d (S)-citalopram and 10mg/d (R)-citalopram), or placebo. Subjects performed an emotional face discrimination task, while undergoing functional magnetic resonance imaging (fMRI) scanning at 3 Tesla. As hypothesized, the OFC, in the context of the emotional face discrimination task, exhibited a down-regulatory effect on amygdala activation. This modulatory effect was significantly increased by (S)-citalopram, but not (R)-citalopram. For the first time, this study shows that (1) the differential effects of the two enantiomers (S)- and (R)-citalopram on cortico-limbic connections can be demonstrated by modeling effective connectivity methods, and (2) one of their mechanisms can be linked to an increased inhibition of amygdala activation by the orbitofrontal cortex.

Neurofeedback based on real-time functional magnetic resonance imaging (rt-fMRI) is a novel and rapidly developing research field. It allows for training of voluntary control over localized brain activity and connectivity and has demonstrated promising clinical applications. Because of the rapid technical developments of MRI techniques and the availability of high-performance computing, new methodological advances in rt-fMRI neurofeedback become possible. Here we outline the core components of a novel open-source neurofeedback framework, termed Open NeuroFeedback Training (OpenNFT), which efficiently integrates these new developments. This framework is implemented using Python and Matlab source code to allow for diverse functionality, high modularity, and rapid extendibility of the software depending on the user’s needs. In addition, it provides an easy interface to the functionality of Statistical Parametric Mapping (SPM) that is also open-source and one of the most widely used fMRI data analysis software. We demonstrate the functionality of our new framework by describing case studies that include neurofeedback protocols based on brain activity levels, effective connectivity models, and pattern classification approaches. This open-source initiative provides a suitable framework to actively engage in the development of novel neurofeedback approaches, so that local methodological developments can be easily made accessible to a wider range of users., NeuroImage, 156, ISSN:1053-8119, ISSN:1095-9572

Objectives: Anticipatory processes prepare the organism for upcoming experiences. The aim of this study was to investigate neural responses related to anticipation and processing of painful stimuli occurring with different levels of uncertainty. Experimental design: Twenty-five participants (13 females) took part in an electroencephalography and functional magnetic resonance imaging (fMRI) experiment at separate times. A visual cue announced the occurrence of an electrical painful or nonpainful stimulus, delivered with certainty or uncertainty (50% chance), at some point during the following 15 s. Principal observations: During the first 2 s of the anticipation phase, a strong effect of uncertainty was reflected in a pronounced frontal stimulus-preceding negativity (SPN) and increased fMRI activation in higher visual processing areas. In the last 2 s before stimulus delivery, we observed stimulus-specific preparatory processes indicated by a centroparietal SPN and posterior insula activation that was most pronounced for the certain pain condition. Uncertain anticipation was associated with attentional control processes. During stimulation, the results revealed that unexpected painful stimuli produced the strongest activation in the affective pain processing network and a more pronounced offset-P2. Conclusions: Our results reflect that during early anticipation uncertainty is strongly associated with affective mechanisms and seems to be a more salient event compared to certain anticipation. During the last 2 s before stimulation, attentional control mechanisms are initiated related to the increased salience of uncertainty. Furthermore, stimulus-specific preparatory mechanisms during certain anticipation also shaped the response to stimulation, underlining the adaptive value of stimulus-targeted preparatory activity which is less likely when facing an uncertain event. Hum Brain Mapp 36:744–755, 2015. © 2014 Wiley Periodicals, Inc.

The anticipation of favourable or unfavourable events is a key component in our daily life. However, the temporal dynamics of anticipation processes in relation to brain activation are still not fully understood. A modified version of the monetary incentive delay task was administered during separate functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) sessions in the same 25 participants to assess anticipatory processes with a multi-modal neuroimaging set-up. During fMRI, gain and loss anticipation were both associated with heightened activation in ventral striatum and reward-related areas. EEG revealed most pronounced P300 amplitudes for gain anticipation, whereas CNV amplitudes distinguished neutral from gain and loss anticipation. Importantly, P300, but not CNV amplitudes, were correlated to neural activation in the ventral striatum for both gain and loss anticipation. Larger P300 amplitudes indicated higher ventral striatum blood oxygen level dependent (BOLD) response. Early stimulus evaluation processes indexed by EEG seem to be positively related to higher activation levels in the ventral striatum, indexed by fMRI, which are usually associated with reward processing. The current results, however, point towards a more general motivational mechanism processing salient stimuli during anticipation., Highlights • Monetary incentive delay task was assessed in separate EEG and fMRI sessions. • Both gain and loss anticipation activated well known reward-related areas. • P300 amplitude differentiated reward cue from non-reward cues. • P300 amplitudes positively correlated with BOLD response in the ventral striatum. • Ventral striatum activation associated with general motivational processes.

Despite the importance of the prefrontal-amygdala (AMY) network for emotion processing, valence-dependent coupling within this network remains elusive. In this study, we assessed the effect of emotional valence on brain activity and effective connectivity. We tested which functional pathways within the prefrontal-AMY network are specifically engaged during the processing of emotional valence. Thirty-three healthy adults were examined with functional magnetic resonance imaging while performing a dynamic faces and dynamic shapes matching task. The valence of the facial expressions varied systematically between positive, negative, and neutral across the task. Functional contrasts determined core areas of the emotion processing circuitry, comprising the medial prefrontal cortex (MPFC), the right lateral prefrontal cortex (LPFC), the AMY, and the right fusiform face area (FFA). Dynamic causal modelling demonstrated that the bidirectional coupling within the prefrontal-AMY circuitry is modulated by emotional valence. Additionally, Bayesian model averaging showed significant bottom-up connectivity from the AMY to the MPFC during negative and neutral, but not positive, valence. Thus, our study provides strong evidence for alterations of bottom-up coupling within the prefrontal-AMY network as a function of emotional valence. Thereby our results not only advance the understanding of the human prefrontal-AMY circuitry in varying valence context, but, moreover, provide a model to examine mechanisms of valence-sensitive emotional dysregulation in neuropsychiatric disorders., eNeuro, 6 (4), ISSN:2373-2822

Progressing from 3T to 7 T functional MRI enables marked improvements of human brain imaging in vivo. Although direct comparisons demonstrated advantages concerning blood oxygen level dependent (BOLD) signal response and spatial specificity, these mostly focused on single brain regions with rather simple tasks. Considering that physiological noise also increases with higher field strength, it is not entirely clear whether the advantages of 7T translate equally to the entire brain during tasks which elicit more complex neuronal processing. Therefore, we investigated the difference between 3T and 7 T in response to transcutaneous electrical painful and non-painful stimulation in 22 healthy subjects. For painful stimuli vs. baseline, stronger activations were observed at 7 T in several brain regions including the insula and supplementary motor area, but not the secondary somatosensory cortex (p

Social anxiety disorder (SAD) is characterized by over-reactivity of fear-related circuits in social or performance situations and associated with marked social impairment. We used dynamic causal modeling (DCM), a method to evaluate effective connectivity, to test our hypothesis that SAD patients would exhibit dysfunctions in the amygdala–prefrontal emotion regulation network. Thirteen unmedicated SAD patients and 13 matched healthy controls performed a series of facial emotion and object discrimination tasks while undergoing fMRI. The emotion-processing network was identified by a task-related contrast and motivated the selection of the right amygdala, OFC, and DLPFC for DCM analysis. Bayesian model averaging for DCM revealed abnormal connectivity between the OFC and the amygdala in SAD patients. In healthy controls, this network represents a negative feedback loop. In patients, however, positive connectivity from OFC to amygdala was observed, indicating an excitatory connection. As we did not observe a group difference of the modulatory influence of the FACE condition on the OFC to amygdala connection, we assume a context-independent reduction of prefrontal control over amygdalar activation in SAD patients. Using DCM, it was possible to highlight not only the neuronal dysfunction of isolated brain regions, but also the dysbalance of a distributed functional network.

Functional magnetic resonance imaging (fMRI) has become the primary non-invasive method for investigating the human brain function. With an increasing number of ultra-high field MR systems worldwide possibilities of higher spatial and temporal resolution in combination with increased sensitivity and specificity are expected to advance detailed imaging of distinct cortical brain areas and subcortical structures. One target region of particular importance to applications in psychiatry and psychology is the amygdala. However, ultra-high field magnetic resonance imaging of these ventral brain regions is a challenging endeavor that requires particular methodological considerations. Ventral brain areas are particularly prone to signal losses arising from strong magnetic field inhomogeneities along susceptibility borders. In addition, physiological artifacts from respiration and cardiac action cause considerable fluctuations in the MR signal. Here we show that, despite these challenges, fMRI data from the amygdala may be obtained with high temporal and spatial resolution combined with increased signal-to-noise ratio. Maps of neural activation during a facial emotion discrimination paradigm at 7T are presented and clearly show the gain in percental signal change compared to 3T results, demonstrating the potential benefits of ultra-high field functional MR imaging also in ventral brain areas.

Question Transcranial magnetic stimulation (TMS) has become a promising therapeutic treatment and neuroscientific research tool, yet how it works is not fully understood. We developed a dedicated MR coil array positioned beneath the TMS coil that allows for concurrent stimulation and imaging and flexible positioning while ensuring TMS efficiency, high MR sensitivity and the use of parallel/multiband imaging sequences. Here we aimed to explain acute effects of TMS over left DLPFC using a new online TMS/fMRI setup in combination with advanced imaging and neuronavigation methods. Resting State functional connectivity and DTI Tractography shall further explain resulting activation patterns at a network level. Methods The study was performed on a 3T Tim Trio scanner (Siemens, Erlangen, Germany). The TMS system used included a MagProX100 stimulator and MRi-B91 MR-compatible TMS coil (Magventure, Farum, Denmark). Five right-handed female subjects (age: 28.6 ± 4.3 years) were examined. Functional images were acquired using EPI (echo-planar imaging) sequence with TR/TE = 1000/33 ms, 28 slices, 1.5 × 1.5 × 3mm3. The experimental procedure is depicted in Fig. 1. FMRI data analyses were performed using SPM12. The design matrix comprised four regressors representing different stimulation amplitudes. DTI tractography was performed using DSI Studio. Figure options Download full-size image Download high-quality image (729 K) Download as PowerPoint slide Results TMS led to intensity-dependent activation increase in the left DLPFC and the contralateral DLPFC ( Figure options Download full-size image Download high-quality image (874 K) Download as PowerPoint slide Fig. 2): Higher stimulation intensities evoked higher bilateral activation. ACC showed a more complex response pattern. Resting-state functional connectivity maps using the stimulation target as seed-voxel showed a network very similar to the TMS-derived activation pattern (Fig. 2). DTI tractography provided additional information about the axonal connection between the left DLPFC stimulation site and the right DLPFC activation cluster. Conclusion This is the first study to assess the acute influence of TMS over DLPFC at an individual level, made possible by a dedicated concurrent TMS/fMRI coil array. Here we show a dose-dependent increase in activity not only underneath the stimulation site but also on the contralateral homologous area and apparent mediating responses in the ACC. This network is confirmed by additional resting-state and tractography data.

Question While the precise mechanism of action is still unclear, rTMS is an effective FDA-approved treatment in depression and shows beneficial behavioral effects in a range of pathologies. A better understanding could improve treatment success and reduce the number of non-treatment responders. This study is the first to investigate effectiveness and specificity of rTMS over left DLPFC using a large-scale (n = 60) sham-controlled cross-over design and an unbiased resting-state (RS) approach. Methods 60 healthy subjects (age: 25.01 ± 4.6 years, f/m: 31/29) underwent rTMS DLPFC and sham stimulation (see Fig. 1) Download : Download high-res image (493KB) Download : Download full-size image . Resting state (rs) fMRI scans were acquired before and twice after stimulation. We investigated BOLD signal changes in functional connectivity (fc) following 10 Hz rTMS (24 × 5 s trains, ITI 20s, 1200 pulses @ 90%MT) during a classic resting state paradigm. We examined rsfc changes using an unbiased approach based on a set of 20 well-established resting state networks derived from multicenter-data independent component analysis by Biswal et al. (2010a, http://fcon_1000.projects.nitrc.org ). Results Comparisons between pre and post stimulation revealed that 19 out of a total of 20 IC networks remained unchanged, i.e. showed no statistically significant differences before and after rTMS irrespective of real/sham stimulation (Fig. 2 A, blue) Download : Download high-res image (1MB) Download : Download full-size image . Only one network (IC17, red dashed) which includes the ACC and PFC showed DLPFC rTMS-related connectivity changes (while staying stable throughout the whole procedure in sham session, Fig. 2 B): The ACC had increased connection strength in the post-rTMS scan within this network, particularly with the DLPFC (stimulation site), bilateral insula and striatum. Conclusion For the first time this study shows in a model-free approach that rTMS over left DLPFC modulates functional connectivity within a specific network while other networks stay stable. This network is typically associated with attention, mood, reward processing and psychiatric conditions that are linked to maladaptive changes in these domains. This could have further implications on treatment, screening and treatment response monitoring of psychiatric conditions.

Functional magnetic resonance imaging (fMRI) is currently the primary method for non-invasive functional localization in the brain. With the emergence of MR systems with field strengths of 4 Tesla and above, neuronal activation may be studied with unprecedented accuracy. In this article we present different approaches to use the improved sensitivity and specificity for expanding current fMRT resolution limits in space and time based on several 7 Tesla studies. In addition to the challenges that arise with ultra-high magnetic fields possible solutions will be discussed.

On average, brain network economy represents a trade-off between communication efficiency, robustness, and connection cost, although an analogous understanding on an individual level is largely missing. Evaluating resting-state networks of 42 healthy participants with seven Tesla functional magnetic resonance imaging and graph theory revealed that not even half of all possible connections were common across subjects. The strongest similarities among individuals were observed for interhemispheric and/or short-range connections, which may relate to the essential feature of the human brain to develop specialized systems within each hemisphere. Despite this marked variability in individual network architecture, all subjects exhibited equal small-world properties. Furthermore, interdependency between four major network economy metrics was observed across healthy individuals. The characteristic path length was associated with the clustering coefficient (peak correlation r=0.93), the response to network attacks (r=-0.97), and the physical connection cost in three-dimensional space (r=-0.62). On the other hand, clustering was negatively related to attack response (r=-0.75) and connection cost (r=-0.59). Finally, increased connection cost was associated with better response to attacks (r=0.65). This indicates that functional brain networks with high global information transfer also exhibit strong network resilience. However, it seems that these advantages come at the cost of decreased local communication efficiency and increased physical connection cost. Except for wiring length, the results were replicated on a subsample at three Tesla (n=20). These findings highlight the finely tuned interrelationships between different parameters of brain network economy. Moreover, the understanding of the individual diversity of functional brain network economy may provide further insights in the vulnerability to mental and neurological disorders.

The (fractional) amplitudes of low-frequency fluctuations (f)ALFF are popular measures for the magnitude of low-frequency oscillations in resting-state fMRI (R-fMRI) data. Both measures can be directly derived from the spectral power of R-fMRI time courses. Numerous studies suggest that ALFF and fALFF might be used as biomarkers for a variety of diseases including schizophrenia, major depressive disorder, and obsessive-compulsive disorder. However, the temporal stability of (f)ALFF values, which is of great importance for the application of (f)ALFF both as a biomarker and scaling parameter, has not been studied in detail yet. Here, we quantify the temporal stability, robustness and reproducibility of both ALFF and fALFF maps obtained from R-fMRI data by performing statistical analyses over 55 minute resting-state scans which included a period of NaCl infusion. We also examine the differences of using either raw or standardised (f)ALFF maps. Our analyses show that no significant changes of (f)ALFF values over the 55minute period occur for both raw and standardised (f)ALFF maps. In addition, we demonstrate that raw (f)ALFF maps across subjects are correlated with head motion as quantified via frame-wise displacement, whereas no such correlation is present in standardised (f)ALFF maps. In conclusion, the results of our study show that both ALFF and fALFF qualify as potential biomarkers due to their high temporal stability.

A characterizing symptom of social anxiety disorder (SAD) is increased emotional reactivity towards potential social threat in combination with impaired emotion and stress regulation. While several neuroimaging studies have linked SAD with hyperreactivity in limbic brain regions when exposed to emotional faces, little is known about habituation in both the amygdala and neocortical regulation areas. 15 untreated SAD patients and 15 age- and gender-matched healthy controls underwent functional magnetic resonance imaging during repeated blocks of facial emotion ([Formula: see text]) and object discrimination tasks ([Formula: see text]). Emotion processing networks were defined by a task-related contrast ([Formula: see text]). Linear regression was employed for assessing habituation effects in these regions. In both groups, the employed paradigm robustly activated the emotion processing and regulation network, including the amygdalae and orbitofrontal cortex (OFC). Statistically significant habituation effects were found in the amygdalae, OFC, and pulvinar thalamus of SAD patients. No such habituation was found in healthy controls. Concurrent habituation in the medial OFC and the amygdalae of SAD patients as shown in this study suggests intact functional integrity and successful short-term down-regulation of neural activation in brain areas responsible for emotion processing. Initial hyperactivation may be explained by an insufficient habituation to new stimuli during the first seconds of exposure. In addition, our results highlight the relevance of the orbitofrontal cortex in social anxiety disorders.

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IntroductionSocial anxiety disorder (SAD) refers to persistent fear of social situations in which the person is exposed to possible scrutiny by others. Anxiety disorders are associated with dysbalanced inhibition within the limbic system towards threatening stimuli (Phillips 2003). It has been shown SAD patients are particularly sensitive towards faces displaying harsh emotions (Phan 2006).ObjectivesIn this study we used fMRI to investigate activation differences between 14 SAD patients and 15 matched healthy controls. The subjects performed a facial emotion discrimination paradigm including a control condition using shape discrimination (modified version of Hariri 2002).AimsThe aim of this study was to investigate emotion task-specific differences in brain activation of patients and healthy controls.MethodsAfter clinical assessment, 225 whole-brain volumes (TR = 1.8s) were acquired on a Siemens TRIO 3T MR scanner and analyzed using SPM8.ResultsThe paradigm activated the amygdalae, the fusiform gyri, the posterior cingulate cortex and the orbitofrontal cortex (OFC) (A). There was a hyperactivation of the OFC in patients compared to healthy controls (B). We found no significant difference in the amygdalae or fusiforme gyrus.ConclusionAlthough not in a social threat situation, SAD patients showed more activity in the orbitofrontal cortex. In contrast to other studies we found no differences in other brain areas indicating an optimized control condition. According to the functional coupling between prefrontal areas and the amygdalae, these data are consistent with an increased effort in down-regulating amygdalar activation by the orbitofrontal cortex.

IntroductionCitalopram is a widely applied SSRI in patients suffering from affective disorder. It is a racemic mixture of the S- and R-enantiomer of citalopram, consisting of equal parts of S-citalopram and R-citalopram, respectively. It has been shown that the inhibitory potency in serotonin reuptake of S-citalopram is much higher compared to R-citalopram, and it is assumed that S-citalopram is the main carrier of the antidepressant effect.ObjectivesHere we investigated the effects of the two SSRIs Citalopram (50% S-, 50% R-citalopram) and Escitalopram (100% S-citalopram) on brain networks during emotion processing using pharmacological functional magnetic resonance imaging (fMRI) and dynamic causal modelling (DCM), an advanced tool to investigate functional integration between different brain regions.MethodsOur results are based on a placebo-controlled, randomized, double-blind, cross-over pharmacological study in 16 healthy subjects during three fMRI scanning sessions performing a facial emotional discrimination paradigm (Windischberger, Neuroimage, 2010). 32 models of pharmacological modulation within the amygdalar-parahippocampal-orbitofrontal network were analysed using Bayesian Model Averaging (BMA) as implemented in SPM8.ResultsS-citalopram showed statistically significant modulatory effects on forward amygdala-orbitofrontal and bidirectional amygdala-parahippocampal connections. No significant modulatory effects of R-citalopram were found.ConclusionsThis is the first fMRI study that showed stimulus-specific differential effects of the two enantiomeres R- and S-citalopram at the neural connectivity level. Our results corroborate studies in rats where escitalopram-induced increases in extracellular serotonin levels were found attenuated when R-citalopram was coinjected. Taken together this might explain the response differences between study drugs as demonstrated in previous clinical trials.

IntroductionSeveral fMRI and resting-state connectivity studies have demonstrated alterations in the limbic system and frontal areas in social anxiety disorder (SAD).AimsHere we used high-resolution whole-brain diffusion tensor imaging (DTI) to examine differences in anatomical connectivity between patients and controls in the white matter.MethodsWe examined 14 SAD patients (age 26.3 ± 9.0y) and 15 healthy controls (age 25.6 ± 3.3y) using DTI on a 3T Trio MRI scanner (Siemens, Germany). DTI acquisition with 1.6 mm isotropic resolution was performed in 30 directions and a maximum b-value of 800. Fractional anisotropy (FA) maps were obtained using FSL. Group analysis was performed in SPM8 (two sample t-test).ResultsThe figure shows a coronal slice through the uncinate fasciculus. Arrows point to areas where SAD patients show decreased FA-values compared to controls (p < 0.05). Note that these areas are limited to the uncinate fasciculus and are found bilaterally.ConclusionReduced FA-values indicate a reduction in anatomical connectivity strength. Our study thus clearly shows reduced connectivity strength in the uncinate fasciculus connecting frontal regions with limbic areas as the amygdalae and hippocampus. This reduced structural connectivity supports functional data demonstrating alterations of brain activation in the amygdala and prefrontal regions in social phobia.