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We as humans do not value lives consistently. While we are willing to act for one victim, we often become numb as the number of victims increases. The empathic ability to adopt others’ perspectives is essential for motivating help. However, the perspective-taking ability in our brains seems limited. Using functional MRI, we demonstrated that the core empathy network including the medial prefrontal cortex (mPFC) was more engaged for events happening to a single person than those happening to many people, no matter whether the events were emotionally neutral or negative. In particular, the perspective-taking-related mPFC showed greater and more extended activations for events about one person than those about many people. The mPFC may be the neural marker of why we feel indifferent to the suffering of large numbers of people in humanitarian disasters.

Parkinson's disease (PD) is a neurodegenerative disorder affecting dopaminergic neurons in the substantia nigra leading to dysfunctional cortico-striato-thalamic-cortical loops. In addition to the characteristic motor symptoms, PD patients often show cognitive impairments, affective changes and other non-motor symptoms, suggesting system-wide effects on brain function. Here, we used functional magnetic resonance imaging and graph-theory based analysis methods to investigate altered whole-brain intrinsic functional connectivity in PD patients (n = 37) compared to healthy controls (n = 20). Global network properties indicated less efficient processing in PD. Analysis of brain network modules pointed to increased connectivity within the sensorimotor network, but decreased interaction of the visual network with other brain modules. We found lower connectivity mainly between the cuneus and the ventral caudate, medial orbitofrontal cortex and the temporal lobe. To identify regions of altered connectivity, we mapped the degree of intrinsic functional connectivity both on ROI- and on voxel-level across the brain. Compared to healthy controls, PD patients showed lower connectedness in the medial and middle orbitofrontal cortex. The degree of connectivity was also decreased in the occipital lobe (cuneus and calcarine), but increased in the superior parietal cortex, posterior cingulate gyrus, supramarginal gyrus and supplementary motor area. Our results on global network and module properties indicated that PD manifests as a disconnection syndrome. This was most apparent in the visual network module. The higher connectedness within the sensorimotor module in PD patients may be related to compensation mechanism in order to overcome the functional deficit of the striato-cortical motor loops or to loss of mutual inhibition between brain networks. Abnormal connectivity in the visual network may be related to adaptation and compensation processes as a consequence of altered motor function. Our analysis approach proved sensitive for detecting disease-related localized effects as well as changes in network functions on intermediate and global scale.

To investigate changes in brain network organization and possible neurobehavioral similarities to attention-deficit hyperactivity disorder (ADHD), we measured changes in brain resting-state functional connectivity (rs-fMRI) and cognitive domains in patients with resistance to thyroid hormone β (RTHβ) and compared them with those in healthy control subjects. In this prospective case-control study, twenty-one participants with genetically confirmed RTHβ were matched with 21 healthy controls. The Adult ADHD Self-Report Scale (ASRS-v1.1) and ADHD Rating Scale-IV were used to assess self-reported symptoms of ADHD. A voxel-wise and atlas-based approach was used to identify changes in the brain networks. The RTHβ group reported behavioral symptoms similar to those of ADHD. We found evidence of weaker network integration of the lingual and fusiform gyri in the RTHβ group, which was mainly driven by weaker connectivity to the bilateral insula and supplementary motor cortex. Functional connectivity between regions of the default mode network (angular gyrus/middle temporal gyrus) and regions of the cognitive control network (bilateral middle frontal gyrus) was increased in RTHβ patients compared to healthy controls. Increased connectivity between regions of the default mode network and the dorsolateral prefrontal cortex is frequently reported in ADHD and is interpreted to be associated with deficits in attention. Our finding of weaker connectivity of the lingual gyrus to the bilateral insula (salience network) in RTHβ patients has also been reported previously in ADHD and may reflect decreased habituation to visual stimuli and increased distractibility. Overall, our observations support the notion of neuropsychological similarities between RTHβ and ADHD.

The history of humankind is an epic of cooperation, which is ubiquitous across societies and increasing in scale. Much human cooperation occurs where it is risky to cooperate for mutual benefit because successful cooperation depends on a sufficient level of cooperation by others. Here we show that arginine vasopressin (AVP), a neuropeptide that mediates complex mammalian social behaviors such as pair bonding, social recognition and aggression causally increases humans’ willingness to engage in risky, mutually beneficial cooperation. In two double-blind experiments, male participants received either AVP or placebo intranasally and made decisions with financial consequences in the “Stag hunt” cooperation game. AVP increases humans’ willingness to cooperate. That increase is not due to an increase in the general willingness to bear risks or to altruistically help others. Using functional brain imaging, we show that, when subjects make the risky Stag choice, AVP down-regulates the BOLD signal in the left dorsolateral prefrontal cortex (dlPFC), a risk-integration region, and increases the left dlPFC functional connectivity with the ventral pallidum, an AVP receptor-rich region previously associated with AVP-mediated social reward processing in mammals. These findings show a previously unidentified causal role for AVP in social approach behavior in humans, as established by animal research.

The presence of motor signs and symptoms in Parkinson's disease (PD) is the result of a long-lasting prodromal phase with an advancing neurodegenerative process. The identification of PD patients in an early phase is, however, crucial for developing disease-modifying drugs. The objective of our study is to investigate whether Diffusion Tensor Imaging (DTI) of the Substantia nigra (SN) analyzed by machine learning algorithms (ML) can be used to identify PD patients. Our study proposes the use of computer-aided algorithms and a highly reproducible approach (in contrast to manually SN segmentation) to increase the reliability and accuracy of DTI metrics used for classification. The results of our study do not confirm the feasibility of the DTI approach, neither on a whole-brain level, ROI-labelled analyses, nor when focusing on the SN only. Our study did not provide any evidence to support the hypothesis that DTI-based analysis, in particular of the SN, could be used to identify PD patients correctly.

The hypothalamus and insular cortex play an essential role in the integration of endocrine and homeostatic signals and their impact on food intake. Resting-state functional connectivity alterations of the hypothalamus, posterior insula (PINS) and anterior insula (AINS) are modulated by metabolic states and caloric intake. Nevertheless, a deeper understanding of how these factors affect the strength of connectivity between hypothalamus, PINS and AINS is missing. This study investigated whether effective (directed) connectivity within this network varies as a function of prandial states (hunger vs. satiety) and energy availability (glucose levels and/or hormonal modulation). To address this question, we measured twenty healthy male participants of normal weight twice: once after 36 ​h of fasting (except water consumption) and once under satiated conditions. During each session, resting-state functional MRI (rs-fMRI) and hormone concentrations were recorded before and after glucose administration. Spectral dynamic causal modeling (spDCM) was used to assess the effective connectivity between the hypothalamus and anterior and posterior insula. Using Bayesian model selection, we observed that the same model was identified as the most likely model for each rs-fMRI recording. Compared to satiety, the hunger condition enhanced the strength of the forward connections from PINS to AINS and reduced the strength of backward connections from AINS to PINS. Furthermore, the strength of connectivity from PINS to AINS was positively related to plasma cortisol levels in the hunger condition, mainly before glucose administration. However, there was no direct relationship between glucose treatment and effective connectivity. Our findings suggest that prandial states modulate connectivity between PINS and AINS and relate to theories of interoception and homeostatic regulation that invoke hierarchical relations between posterior and anterior insula. •We use spectral DCM and BMS to test whether prandial states and glucose administration altered EC at rest between hypothalamus and insula.•Hunger (relative to satiety) strengthened forward connections from posterior to anterior insula and reduced backward connections between these same areas.•In the hunger before glucose administration, connection strength from right posterior to anterior insula was positively associated with cortisol levels.

Resting-state functional magnetic resonance imaging (rs-fMRI) has become an essential measure to investigate the human brain's spontaneous activity and intrinsic functional connectivity. Several studies including our own previous work have shown that the brain controls the regulation of energy expenditure and food intake behavior. Accordingly, we expected different metabolic states to influence connectivity and activity patterns in neuronal networks. The influence of hunger and satiety on rs-fMRI was investigated using three connectivity models (local connectivity, global connectivity and amplitude rs-fMRI signals). After extracting the connectivity parameters of 90 brain regions for each model, we used sequential forward floating selection strategy in conjunction with a linear support vector machine classifier and permutation tests to reveal which connectivity model differentiates best between metabolic states (hunger vs. satiety). We found that the amplitude of rs-fMRI signals is slightly more precise than local and global connectivity models in order to detect resting brain changes during hunger and satiety with a classification accuracy of 81%. The amplitude of rs-fMRI signals serves as a suitable basis for machine learning based classification of brain activity. This opens up the possibility to apply this combination of algorithms to similar research questions, such as the characterization of brain states (e.g., sleep stages) or disease conditions (e.g., Alzheimer's disease, minimal cognitive impairment).

Background The vagus nerve plays an important role in the regulation of food intake. Modulating vagal activity via electrical stimulation (VNS) in patients and animal studies caused changes in food intake, energy metabolism, and body weight. However, the moderating impact of cognitive processes on VNS effects on eating behavior, has not been investigated so far. Hypothesis We hypothesized that transcutaneous VNS (tVNS) affects food intake by altering cognitive functions relevant to the processing of food-related information. Methods Using a repeated measurement design, we applied tVNS and a sham stimulation for 2h on two different days in normal-weight subjects. We recorded standard scalp EEG while subjects watched food and object pictures presented in an oddball-task. We analyzed the event-related potentials (ERPs) P1, P2, N2, and LPP, and also examined the amount of consumed food and eating duration in a free-choice test meal. Results Significant differences between stimulations were observed for the P1, P2, and N2 amplitudes. However, we found no tVNS dependent modulation of food intake nor a specific food-related stimulation effect on the ERPs. Further analyses revealed a negative relationship between P2-amplitude and food intake for the sham stimulation. Significant effects are additionally confirmed by Bayesian statistics. Conclusion Our study demonstrates tVNS’ impact on visual processing. Since the effects were similar between food and object stimuli, a general effect on visual perceptual processing can be assumed. More detailed investigations of these effects and their relationship with food intake and metabolism seem reasonable for future studies.

Present project is concerned with the possibility to modulate the neural regulation of food intake by non-invasive stimulation of the vagus nerve. This nerve carries viscero-afferent information from the gut and other internal organs and therefore serves an important role in ingestive behavior. The electrical stimulation of the vagus nerve (VNS) is a qualified procedure in the treatment of drug-resistant epilepsy and depression. Since weight loss is a known common side effect of VNS treatment in patients with implanted devices, VNS is evaluated as a treatment of obesity. To investigate potential VNS-related changes in the cognitive processing of food-related items, 21 healthy participants were recorded in a 3-Tesla scanner in two counterbalanced sessions. Participants were presented with 72 food pictures and asked to rate how much they liked that food. Before entering the scanner subjects received a 1-h sham or verum stimulation, which was implemented transcutanously with a Cerbomed NEMOS ® device. We found significant activations in core areas of the vagal afferent pathway, including left brainstem, thalamus, temporal pole, amygdala, insula, hippocampus, and supplementary motor area for the interaction between ratings (high vs low) and session (verum vs sham stimulation). Significant activations were also found for the main effect of verum compared to sham stimulation in the left inferior and superior parietal cortex. These results demonstrate an effect of tVNS on food image processing even with a preceding short stimulation period. This is a necessary prerequisite for a therapeutic application of tVNS which has to be evaluated in longer-term studies.

To study the interplay of metabolic state (hungry vs. satiated) and glucose administration (including hormonal modulation) on brain function, resting-state functional magnetic resonance imaging (rs-fMRI) and blood samples were obtained in 24 healthy normal-weight men in a repeated measurement design. Participants were measured twice: once after a 36 h fast (except water) and once under satiation (three meals/day for 36 h). During each session, rs-fMRI and hormone concentrations were recorded before and after a 75 g oral dose of glucose. We calculated the amplitude map from blood-oxygen-level-dependent (BOLD) signals by using the fractional amplitude of low-frequency fluctuation (fALFF) approach for each volunteer per condition. Using multiple linear regression analysis (MLRA) the interdependence of brain activity, plasma insulin and blood glucose was investigated. We observed a modulatory impact of fasting state on intrinsic brain activity in the posterior cingulate cortex (PCC). Strikingly, differences in plasma insulin levels between hunger and satiety states after glucose administration at the time of the scan were negatively related to brain activity in the posterior insula and superior frontal gyrus (SFG), while plasma glucose levels were positively associated with activity changes in the fusiform gyrus. Furthermore, we could show that changes in plasma insulin enhanced the connectivity between the posterior insula and SFG. Our results indicate that hormonal signals like insulin alleviate an acute hemostatic energy deficit by modifying the homeostatic and frontal circuitry of the human brain.