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Neuser, M. P.

Publications and source records attributed to Neuser, M. P..

6 recordsLinked to original sources

Brain signaling dynamics after vagus nerve stimulation

The vagus nerve projects to a well-defined neural circuit via the nucleus tractus solitarii (NTS) and its stimulation elicits a wide range of metabolic, neuromodulatory, and behavioral effects. Transcutaneous vagus nerve stimulation (tVNS) has been established as a promising technique to non-invasively alter brain function. However, the precise dynamics elicited by tVNS in humans are still largely unknown. Here, we performed fMRI with concurrent right-sided tVNS (vs. sham) following a randomized cross-over design (N=40). First, to unravel the temporal profile of tVNS-induced changes in the NTS, we compared fMRI time series to canonical profiles for stimulation ON and OFF cycles. Model comparisons indicated that NTS time series were best fit by block-wise shifts in signal amplitude with stimulation ON and OFF estimates being highly correlated. Therefore, we compared stimulation (ON + OFF) versus baseline phases and found that tVNS increased fMRI BOLD activation in the NTS, but this effect was dependent on sufficient temporal signal-to-noise ratio (tSNR) in the mask. Second, to identify the spatiotemporal evolution of tVNS-induced changes in the brain, we examined lagged co-activation patterns and phase coherence. In contrast to our hypothesis, tVNS did not alter dynamic functional connectivity after correction for multiple comparisons. Third, to establish a positive control for future research, we measured changes in gastric myoelectrical frequency via an electrogastrogram. Again, in contrast to our hypothesis, tVNS induced no changes in gastric frequency. Collectively, our study provides evidence that tVNS can perturb brain signaling in the NTS, but these effects are dependent on tSNR and require precise localization. In light of an absence of acute tVNS-induced effects on dynamic functional connectivity and gastric motility, we discuss which steps are necessary to advance future research on afferent and efferent effects of tVNS.

neuroscience↗

Influenca: a gamified assessment of value-based decision-making for longitudinal studies

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. Here, we developed an open-source cross-platform application Influenca that provides a novel reward learning task complemented by ecological momentary assessment (EMA) for repeated assessment over weeks. In this task, players have to identify the most effective medication by selecting the best option after integrating offered points with changing probabilities (according to random Gaussian walks). Participants can complete up to 31 levels with 150 trials each. To encourage replay on their preferred device, in-game screens provide feedback on the progress. Using an initial validation sample of 127 players (2904 runs), we found that reinforcement learning parameters such as the learning rate and reward sensitivity show low to medium intra-class correlations (ICC: 0.22-0.52), indicating substantial within- and between-subject variance. Notably, state items 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.

neuroscience↗

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 (MBMI= 23.0 kg/m2 {+/-} 2.95) 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, rp(78) = -.28, p = .011 (controlled for average effort). In line with previous findings, higher wanting variability was associated with higher BMI, rp(78) = .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.

neuroscience↗

Vagus nerve stimulation increases vigor 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 and enhances dopamine transmission 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 the right ear using a randomized cross-over design (vs. sham). During stimulation, 81 healthy participants had to exert effort to earn food or monetary rewards. We reasoned that taVNS enhances motivation and tested whether it does so by increasing prospective benefits (i.e., vigor) or reducing costs of action (i.e., maintenance) compared to sham stimulation. In line with preclinical studies, taVNS generally enhanced invigoration of effort (p = .004, Bayes factor, BF10 = 7.34), whereas stimulation on the left side primarily facilitated vigor for food rewards (left taVNS: Stimulation x Reward Type, p =.003, BF10 = 11.80). In contrast, taVNS did not affect effort maintenance (ps [&ge;] .09, BF10 < 0.52). Critically, during taVNS, vigor declined less steeply with decreases in wanting ({Delta}b = -.046, p = .031) indicating a boost in the drive to work for rewards. Collectively, our results suggest that taVNS enhances reward-seeking by boosting vigor, not effort maintenance and that the side of the stimulation affects generalization beyond food reward. We conclude that taVNS may enhance the pursuit of prospective rewards which may pave new avenues for treatment of motivational deficiencies.

neuroscience↗

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.

neuroscience↗

Stimulation of the vagus nerve reduces learning in a go/no-go reinforcement learning task

When facing decisions to approach rewards or to avoid punishments, we often figuratively go with our gut, and the impact of metabolic states such as hunger on motivation are well documented. However, whether and how vagal feedback signals from the gut influence instrumental actions is unknown. Here, we investigated the effect of non-invasive transcutaneous vagus nerve stimulation (tVNS) vs. sham (randomized cross-over design) on approach and avoidance behavior using an established go/no-go reinforcement learning paradigm (Guitart-Masip et al., 2012) in 39 healthy, participants after an overnight fast. First, mixed-effects logistic regression analysis of choice accuracy showed that tVNS acutely impaired decision-making, p = .045. Computational reinforcement learning models identified the cause of this as a reduction in the learning rate through tVNS ({Delta} = -0.092, pboot= .002), particularly after punishment ({Delta}Pun= -0.081, pboot= .012 vs.{Delta} Rew= -0.031, p = .22). However, tVNS had no effect on go biases, Pavlovian response biases or response time. Hence, tVNS appeared to influence learning rather than action execution. These results highlight a novel role of vagal afferent input in modulating reinforcement learning by tuning the learning rate according to homeostatic needs.

neuroscience↗