Mechanisms for survival: vagal control of goal-directed behavior

Survival is a fundamental physiological drive, and neural circuits have evolved to prioritize actions that meet the energy demands of the body. This fine-tuning of goal-directed actions based on metabolic states ('allostasis') is deeply rooted in our brain, and hindbrain nuclei orchestrate the vital communication between the brain and body through the vagus nerve. Despite mounting evidence for vagal control of allostatic behavior in animals, its broader function in humans is still contested. Based on stimulation studies, we propose that the vagal afferent pathway supports transitions between survival modes by gating the integration of ascending bodily signals, thereby regulating reward-seeking. By reconceptualizing vagal signals as catalysts for goal-directed behavior, our perspective opens new avenues for theory-driven translational work in mental disorders.

Reliability of gamified reinforcement learning in densely sampled longitudinal assessments

Reinforcement learning is a core facet of motivation and alterations have been associated with various mental disorders. To build better models of individual learning, repeated measurement of value-based decision-making is crucial. However, the focus on lab-based assessment of reward learning has limited the number of measurements and the test-retest reliability of many decision-related parameters is therefore unknown. In this paper, we present an open-source cross-platform application Influenca that provides a novel reward learning task complemented by ecological momentary assessment (EMA) of current mental and physiological states for repeated assessment over weeks. In this task, players have to identify the most effective medication by integrating reward values with changing probabilities to win (according to random Gaussian walks). Participants can complete up to 31 runs with 150 trials each. To encourage replay, in-game screens provide feedback on the progress. Using an initial validation sample of 384 players (9729 runs), we found that reinforcement learning parameters such as the learning rate and reward sensitivity show poor to fair intra-class correlations (ICC: 0.22-0.53), indicating substantial within- and between-subject variance. Notably, items assessing the psychological state showed comparable ICCs as reinforcement learning parameters. To conclude, our innovative and openly customizable app framework provides a gamified task that optimizes repeated assessments of reward learning to better quantify intra- and inter-individual differences in value-based decision-making over time.

Resting-state functional connectivity patterns associated with childhood maltreatment in a large bicentric cohort of adults with and without major depression

BACKGROUND

Childhood maltreatment (CM) represents a potent risk factor for major depressive disorder (MDD), including poorer treatment response. Altered resting-state connectivity in the fronto-limbic system has been reported in maltreated individuals. However, previous results in smaller samples differ largely regarding localization and direction of effects.

METHODS

We included healthy and depressed samples [n = 624 participants with MDD; n = 701 healthy control (HC) participants] that underwent resting-state functional MRI measurements and provided retrospective self-reports of maltreatment using the Childhood Trauma Questionnaire. A-priori defined regions of interest [ROI; amygdala, hippocampus, anterior cingulate cortex (ACC)] were used to calculate seed-to-voxel connectivities.

RESULTS

No significant associations between maltreatment and resting-state connectivity of any ROI were found across MDD and HC participants and no interaction effect with diagnosis became significant. Investigating MDD patients only yielded maltreatment-associated increased connectivity between the amygdala and dorsolateral frontal areas [pFDR < 0.001; η2partial = 0.050; 95%-CI (0.023-0.085)]. This effect was robust across various sensitivity analyses and was associated with concurrent and previous symptom severity. Particularly strong amygdala-frontal associations with maltreatment were observed in acutely depressed individuals [n = 264; pFDR < 0.001; η2partial = 0.091; 95%-CI (0.038-0.166)). Weaker evidence - not surviving correction for multiple ROI analyses - was found for altered supracallosal ACC connectivity in HC individuals associated with maltreatment.

CONCLUSIONS

The majority of previous resting-state connectivity correlates of CM could not be replicated in this large-scale study. The strongest evidence was found for clinically relevant maltreatment associations with altered adult amygdala-dorsolateral frontal connectivity in depression. Future studies should explore the relevance of this pathway for a maltreated subgroup of MDD patients.

Producing Open Data

Open data offer the opportunity to economically combine data into large-scale datasets, fostering collaboration and re-use in the interest of treating researchers’ resources as well as study participants with care. Whereas advantages of utilising open data might be self-evident, the production of open datasets also challenges individual researchers. This is especially true for open data that include personal data, for which higher requirements have been legislated. Mainly building on our own experience as scholars from different research traditions (life sciences, social sciences and humanities), we describe best-practice approaches for opening up research data. We reflect on common barriers and strategies to overcome them, condensed into a step-by-step guide focused on actionable advice in order to mitigate the costs and promote the benefit of open data on three levels at once: society, the disciplines and individual researchers. Our contribution may prevent researchers and research units from re-inventing the wheel when opening data and enable them to learn from our experience.

Functional Connectivity of the Nucleus Accumbens and Changes in Appetite in Patients With Depression

Importance

Major depressive disorder (MDD) is characterized by a substantial burden on health, including changes in appetite and body weight. Heterogeneity of depressive symptoms has hampered the identification of biomarkers that robustly generalize to most patients, thus calling for symptom-based mapping.

Objective

To define the functional architecture of the reward circuit subserving increases vs decreases in appetite and body weight in patients with MDD by specifying their contributions and influence on disease biomarkers using resting-state functional connectivity (FC).

Design, Setting, and Participants

In this case-control study, functional magnetic resonance imaging (fMRI) data were taken from the Marburg-Münster FOR 2107 Affective Disorder Cohort Study (MACS), collected between September 2014 and November 2016. Cross-sectional data of patients with MDD (n = 407) and healthy control participants (n = 400) were analyzed from March 2018 to June 2022.

Main Outcomes and Measures

Changes in appetite during the depressive episode and their association with FC were examined using fMRI. By taking the nucleus accumbens (NAcc) as seed of the reward circuit, associations with opposing changes in appetite were mapped, and a sparse symptom-specific elastic-net model was built with 10-fold cross-validation.

Results

Among 407 patients with MDD, 249 (61.2%) were women, and the mean (SD) age was 36.79 (13.4) years. Reduced NAcc-based FC to the ventromedial prefrontal cortex (vmPFC) and the hippocampus was associated with reduced appetite (vmPFC: bootstrap r = 0.13; 95% CI, 0.02-0.23; hippocampus: bootstrap r = 0.15; 95% CI, 0.05-0.26). In contrast, reduced NAcc-based FC to the insular ingestive cortex was associated with increased appetite (bootstrap r = -0.14; 95% CI, -0.24 to -0.04). Critically, the cross-validated elastic-net model reflected changes in appetite based on NAcc FC and explained variance increased with increasing symptom severity (all patients: bootstrap r = 0.24; 95% CI, 0.16-0.31; patients with Beck Depression Inventory score of 28 or greater: bootstrap r = 0.42; 95% CI, 0.25-0.58). In contrast, NAcc FC did not classify diagnosis (MDD vs healthy control).

Conclusions and Relevance

In this study, NAcc-based FC reflected important individual differences in appetite and body weight in patients with depression that can be leveraged for personalized prediction. However, classification of diagnosis using NAcc-based FC did not exceed chance levels. Such symptom-specific associations emphasize the need to map biomarkers onto more confined facets of psychopathology to improve the classification and treatment of MDD.

Non-invasive vagus nerve stimulation boosts mood recovery after effort exertion

BACKGROUND

Mood plays an important role in our life which is illustrated by the disruptive impact of aberrant mood states in depression. Although vagus nerve stimulation (VNS) has been shown to improve symptoms of depression, the exact mechanism is still elusive, and it is an open question whether non-invasive VNS could be used to swiftly and robustly improve mood.

METHODS

Here, we investigated the effect of left- and right-sided transcutaneous auricular VNS (taVNS) v. a sham control condition on mood after the exertion of physical and cognitive effort in 82 healthy participants (randomized cross-over design) using linear mixed-effects and hierarchical Bayesian analyses of mood ratings.

RESULTS

We found that 90 min of either left-sided or right-sided taVNS improved positive mood [b = 5.11, 95% credible interval, CI (1.39-9.01), 9.6% improvement relative to the mood intercept, BF₁₀ = 7.69, p_LME = 0.017], yet only during the post-stimulation phase. Moreover, lower baseline scores of positive mood were associated with greater taVNS-induced improvements in motivation [r = -0.42, 95% CI (-0.58 to -0.21), BF₁₀ = 249].

CONCLUSIONS

We conclude that taVNS boosts mood after a prolonged period of effort exertion with concurrent stimulation and that acute motivational effects of taVNS are partly dependent on initial mood states. Collectively, our results show that taVNS may help quickly improve affect after a mood challenge, potentially by modulating interoceptive signals contributing to the reappraisal of effortful behavior. This suggests that taVNS could be a useful add-on to current behavioral therapies.

Does transcutaneous auricular vagus nerve stimulation affect vagally mediated heart rate variability? A living and interactive Bayesian meta-analysis

Non-invasive brain stimulation techniques, such as transcutaneous auricular vagus nerve stimulation (taVNS), have considerable potential for clinical use. Beneficial effects of taVNS have been demonstrated on symptoms in patients with mental or neurological disorders as well as transdiagnostic dimensions, including mood and motivation. However, since taVNS research is still an emerging field, the underlying neurophysiological processes are not yet fully understood, and the replicability of findings on biomarkers of taVNS effects has been questioned. The objective of this analysis was to synthesize the current evidence concerning the effects of taVNS on vagally mediated heart rate variability (vmHRV), a candidate biomarker that has, so far, received most attention in the field. We performed a living Bayesian random effects meta-analysis. To keep the synthesis of evidence transparent and up to date as new studies are being published, we developed a Shiny web app that regularly incorporates new results and enables users to modify study selection criteria to evaluate the robustness of the inference across potential confounds. Our analysis focuses on 16 single-blind studies comparing taVNS versus sham in healthy participants. The meta-analysis provides strong evidence for the null hypothesis (g = 0.014, CI_shortest = [-0.103, 0.132], BF₀₁ = 24.678), indicating that acute taVNS does not alter vmHRV compared to sham. To conclude, there is no support for the hypothesis that vmHRV is a robust biomarker for acute taVNS. By increasing transparency and timeliness, the concept of living meta-analyses can lead to transformational benefits in emerging fields such as non-invasive brain stimulation.

International Consensus Based Review and Recommendations for Minimum Reporting Standards in Research on Transcutaneous Vagus Nerve Stimulation (Version 2020)

Given its non-invasive nature, there is increasing interest in the use of transcutaneous vagus nerve stimulation (tVNS) across basic, translational and clinical research. Contemporaneously, tVNS can be achieved by stimulating either the auricular branch or the cervical bundle of the vagus nerve, referred to as transcutaneous auricular vagus nerve stimulation(VNS) and transcutaneous cervical VNS, respectively. In order to advance the field in a systematic manner, studies using these technologies need to adequately report sufficient methodological detail to enable comparison of results between studies, replication of studies, as well as enhancing study participant safety. We systematically reviewed the existing tVNS literature to evaluate current reporting practices. Based on this review, and consensus among participating authors, we propose a set of minimal reporting items to guide future tVNS studies. The suggested items address specific technical aspects of the device and stimulation parameters. We also cover general recommendations including inclusion and exclusion criteria for participants, outcome parameters and the detailed reporting of side effects. Furthermore, we review strategies used to identify the optimal stimulation parameters for a given research setting and summarize ongoing developments in animal research with potential implications for the application of tVNS in humans. Finally, we discuss the potential of tVNS in future research as well as the associated challenges across several disciplines in research and clinical practice.

Can't decide how much to EAT? Effort variability for reward is associated with cognitive restraint

Food intake is inherently variable and often characterized by episodical restraint or overeating (uncontrolled eating). Such heightened variability in intake has been associated with higher variability in the brain response to food reward, but it is an open issue whether comparable associations with elevated variability in reward seeking exist. Here, we assessed whether restraint and uncontrolled eating as markers of trait-like variability in eating are associated with higher intra-individual variability in reward seeking as captured by a cost-benefit paradigm. To test this hypothesis, 81 healthy, overnight-fasting participants (M_BMI = 23.0 kg/m² ± 3.0) completed an effort allocation task (EAT) twice. In the EAT, participants had to exert physical effort to earn monetary and food rewards and indicated levels of wanting through visual analog scales (VAS). As predicted, we found that greater trial-by-trial effort variability was associated with lower scores on cognitive restraint, r_p(78) = -0.28, p = .011 (controlled for average effort). In line with previous findings, higher wanting variability was associated with higher BMI, r_p(78) = 0.25, p = .026 (controlled for average effort). Collectively, our results support the idea that higher variability in reward seeking is a potential risk factor for eating beyond homeostatic need. Since associations with variability measures of reward exceeded associations with average reward seeking, our findings may indicate that variability in the representation of the reward value could be a crucial aspect driving fluctuations in food intake.

Localized Prediction of Glutamate from Whole-Brain Functional Connectivity of the Pregenual Anterior Cingulate Cortex

Local measures of neurotransmitters provide crucial insights into neurobiological changes underlying altered functional connectivity in psychiatric disorders. However, noninvasive neuroimaging techniques such as magnetic resonance spectroscopy (MRS) may cover anatomically and functionally distinct areas, such as p32 and p24 of the pregenual anterior cingulate cortex (pgACC). Here, we aimed to overcome this low spatial specificity of MRS by predicting local glutamate and GABA based on functional characteristics and neuroanatomy in a sample of 88 human participants (35 females), using complementary machine learning approaches. Functional connectivity profiles of pgACC area p32 predicted pgACC glutamate better than chance (R2 = 0.324) and explained more variance compared with area p24 using both elastic net and partial least-squares regression. In contrast, GABA could not be robustly predicted. To summarize, machine learning helps exploit the high resolution of fMRI to improve the interpretation of local neurometabolism. Our augmented multimodal imaging analysis can deliver novel insights into neurobiology by using complementary information.SIGNIFICANCE STATEMENT Magnetic resonance spectroscopy (MRS) measures local glutamate and GABA noninvasively. However, conventional MRS requires large voxels compared with fMRI, because of its inherently low signal-to-noise ratio. Consequently, a single MRS voxel may cover areas with distinct cytoarchitecture. In the largest multimodal 7 tesla machine learning study to date, we overcome this limitation by capitalizing on the spatial resolution of fMRI to predict local neurotransmitters in the PFC. Critically, we found that prefrontal glutamate could be robustly and exclusively predicted from the functional connectivity fingerprint of one of two anatomically and functionally defined areas that form the pregenual anterior cingulate cortex. Our approach provides greater spatial specificity on neurotransmitter levels, potentially improving the understanding of altered functional connectivity in mental disorders.

Evidence for modulation of EEG microstate sequence by vigilance level

The momentary global functional state of the brain is reflected in its electric field configuration and cluster analytical approaches have consistently shown four configurations, referred to as EEG microstate classes A to D. Changes in microstate parameters are associated with a number of neuropsychiatric disorders, task performance, and mental state establishing their relevance for cognition. However, the common practice to use eye-closed resting state data to assess the temporal dynamics of microstate parameters might induce systematic confounds related to vigilance levels. Here, we studied the dynamics of microstate parameters in two independent data sets and showed that the parameters of microstates are strongly associated with vigilance level assessed both by EEG power analysis and fMRI global signal. We found that the duration and contribution of microstate class C, as well as transition probabilities towards microstate class C were positively associated with vigilance, whereas the sign was reversed for microstate classes A and B. Furthermore, in looking for the origins of the correspondence between microstates and vigilance level, we found Granger-causal effects of vigilance levels on microstate sequence parameters. Collectively, our findings suggest that duration and occurrence of microstates have a different origin and possibly reflect different physiological processes. Finally, our findings indicate the need for taking vigilance levels into consideration in resting-sate EEG investigations.

Vagus nerve stimulation boosts the drive to work for rewards

Interoceptive feedback transmitted via the vagus nerve plays a vital role in motivation by tuning actions according to physiological needs. Whereas vagus nerve stimulation (VNS) reinforces actions in animals, motivational effects elicited by VNS in humans are still largely elusive. Here, we applied non-invasive transcutaneous auricular VNS (taVNS) on the left or right ear while participants exerted effort to earn rewards using a randomized cross-over design (vs. sham). In line with preclinical studies, acute taVNS enhances invigoration of effort, and stimulation on the left side primarily facilitates invigoration for food rewards. In contrast, we do not find conclusive evidence that acute taVNS affects effort maintenance or wanting ratings. Collectively, our results suggest that taVNS enhances reward-seeking by boosting invigoration, not effort maintenance and that the stimulation side affects generalization beyond food reward. Thus, taVNS may enhance the pursuit of prospective rewards which may pave avenues to treat motivational deficiencies.

The vagus nerve transmits signals between the gut and the brain thereby tuning motivated behavior to physiological needs. Here, the authors show that acute non-invasive stimulation of the vagus nerve via the ear enhances the invigoration of effort for rewards.

Non-invasive stimulation of vagal afferents reduces gastric frequency

Metabolic feedback between the gut and the brain relayed via the vagus nerve contributes to energy homeostasis. We investigated in healthy adults whether non-invasive stimulation of vagal afferents impacts energy homeostasis via efferent effects on metabolism or digestion. In a randomized crossover design, we applied transcutaneous auricular vagus nerve stimulation (taVNS) while recording efferent metabolic effects using simultaneous electrogastrography (EGG) and indirect calorimetry. We found that taVNS reduced gastric myoelectric frequency (p = .008), but did not alter resting energy expenditure. We conclude that stimulating vagal afferents induces gastric slowing via vagal efferents without acutely affecting net energy expenditure at rest. Collectively, this highlights the potential of taVNS to modulate digestion by activating the dorsal vagal complex. Thus, taVNS-induced changes in gastric frequency are an important peripheral marker of brain stimulation effects.

The anterior insula channels prefrontal expectancy signals during affective processing

Expectancy shapes our perception of impending events. Although such an interplay between cognitive and affective processes is often impaired in mental disorders, it is not well understood how top-down expectancy signals modulate future affect. We therefore track the information flow in the brain during cognitive and affective processing segregated in time using task-specific cross-correlations. Participants in two independent fMRI studies (N₁ = 37 & N₂ = 55) were instructed to imagine a situation with affective content as indicated by a cue, which was then followed by an emotional picture congruent with expectancy. To correct for intrinsic covariance of brain function, we calculate resting-state cross-correlations analogous to the task. First, using factorial modeling of delta cross-correlations (task-rest) of the first study, we find that the magnitude of expectancy signals in the anterior insula cortex (AIC) modulates the BOLD response to emotional pictures in the anterior cingulate and dorsomedial prefrontal cortex in opposite directions. Second, using hierarchical linear modeling of lagged connectivity, we demonstrate that expectancy signals in the AIC indeed foreshadow this opposing pattern in the prefrontal cortex. Third, we replicate the results in the second study using a higher temporal resolution, showing that our task-specific cross-correlation approach robustly uncovers the dynamics of information flow. We conclude that the AIC arbitrates the recruitment of distinct prefrontal networks during cued picture processing according to triggered expectations. Taken together, our study provides new insights into neuronal pathways channeling cognition and affect within well-defined brain networks. Better understanding of such dynamics could lead to new applications tracking aberrant information processing in mental disorders.

Addressing the reliability fallacy in fMRI: Similar group effects may arise from unreliable individual effects

To cast valid predictions of future behavior or diagnose disorders, the reliable measurement of a "biomarker" such as the brain activation to prospective reward is a prerequisite. Surprisingly, only a small fraction of functional magnetic resonance imaging (fMRI) studies report or cite the reliability of brain activation maps involved in group analyses. Here, using simulations and exemplary longitudinal data of 126 healthy adolescents performing an intertemporal choice task, we demonstrate that reproducing a group activation map over time is not a sufficient indication of reliable measurements at the individual level. Instead, selecting regions based on significant main effects at the group level may yield estimates that fail to reliably capture individual variance in the subjective evaluation of an offer. Collectively, our results call for more attention on the reliability of supposed biomarkers at the level of the individual. Thus, caution is warranted in employing brain activation patterns prematurely for clinical applications such as diagnosis or tailored interventions before their reliability has been conclusively established by large-scale studies. To facilitate assessing and reporting of the reliability of fMRI contrasts in future studies, we provide a toolbox that incorporates common measures of global and local reliability.

Higher interference susceptibility in reaction time task is accompanied by weakened functional dissociation between salience and default mode network

BACKGROUND

The relationship between task-positive and task-negative components of brain networks has repeatedly been shown to be characterized by dissociated fluctuations of spontaneous brain activity. We tested whether the interaction between task-positive and task-negative brain areas during resting-state predicts higher interference susceptibility, i.e. increased reaction times (RTs), during an Attention Modulation by Salience Task (AMST).

METHODS

29 males underwent 3T resting-state Magnetic Resonance Imaging scanning. Subsequently, they performed the AMST, which measures RTs to early- and late-onset auditory stimuli while perceiving high- or low-salient visual distractors. We conducted seed-based resting-state functional connectivity (rsFC) analyses using global signal correction. We assessed general responsiveness and salience related interference in the AMST and set this into context of the resting-state functional connectivity (rsFC) between a key salience network region (dACC; task-positive region) and a key default mode network region (precuneus; task-negative region).

RESULTS

With increasing RTs to high- but not low-salient pictures dACC shows significantly weakened functional dissociation to a cluster in precuneus. This cluster overlaps with a cluster that correlates in its dACC rsFC with subjects' interference, as measured of high-salient RTs relative to low-salient RTs.

CONCLUSION

Our findings suggest that the interaction between salience network (SN) and default mode network (DMN) at rest predicts susceptibility to distraction. Subjects, that are more susceptible to high-salient stimuli - task-irrelevant external information - showed increased dACC rsFC toward precuneus. This is consistent with prior work in individuals with impaired attentional focus. Future studies might help to conclude whether an increased rsFC between a SN region and DMN region may serve as a predictor for clinical syndromes characterized by attentional impairments, e.g. ADHD. This could lead to an alternative, objective diagnosis and treatment of such disorders by decreasing the rsFC of these regions.

How to trust a perfect stranger: predicting initial trust behavior from resting-state brain-electrical connectivity

Reciprocal exchanges can be understood as the updating of an initial belief about a partner. This initial level of trust is essential when it comes to establishing cooperation with an unknown partner, as cooperation cannot arise without a minimum of trust not justified by previous successful exchanges with this partner. Here we demonstrate the existence of a representation of the initial trust level before an exchange with a partner has occurred. Specifically, we can predict the Investor's initial investment--i.e. his initial level of trust toward the unknown trustee in Round 1 of a standard 10-round Trust Game-from resting-state functional connectivity data acquired several minutes before the start of the Trust Game. Resting-state functional connectivity is, however, not significantly associated with the level of trust in later rounds, potentially mirroring the updating of the initial belief about the partner. Our results shed light on how the initial level of trust is represented. In particular, we show that a person's initial level of trust is, at least in part, determined by brain electrical activity acquired well before the beginning of an exchange.