The neural underpinnings of anorexia nervosa (AN) are poorly understood. Results from existing functional brain imaging studies using disorder-relevant food- or body-stimuli have been heterogeneous and may be biased due to varying compliance or strategies of the participants. In this study, resting state functional connectivity imaging was used. To explore the distributed nature and complexity of brain function we characterized network patterns in patients with acute AN. Thirty-five unmedicated female acute AN patients and 35 closely matched healthy female participants underwent resting state functional magnetic resonance imaging. We used a network-based statistic (NBS) approach [Zalesky et al., 2010a] to identify differences between groups by isolating a network of interconnected nodes with a deviant connectivity pattern. Group comparison revealed a subnetwork of connections with decreased connectivity including the amygdala, thalamus, fusiform gyrus, putamen and the posterior insula as the central hub in the patient group. Results were not driven by changes in intranodal or global connectivity. No network could be identified where AN patients had increased coupling. Given the known involvement of the identified thalamo-insular subnetwork in interoception, decreased connectivity in AN patients in these nodes might reflect changes in the propagation of sensations that alert the organism to urgent homeostatic imbalances and pain-processes that are known to be severely disturbed in AN and might explain the striking discrepancy between patient's actual and perceived internal body state.

No abstract

Low image sampling rates used in resting state functional magnetic resonance imaging (rs-fMRI) may cause aliasing of the cardiorespiratory pulsations over the very low frequency (VLF) BOLD signal fluctuations which reflects to functional connectivity (FC). In this study, we examine the effect of sampling rate on currently used rs-fMRI FC metrics. Ultra-fast fMRI magnetic resonance encephalography (MREG) data, sampled with TR 0.1 s, was downsampled to different subsampled repetition times (sTR, range 0.3–3 s) for comparisons. Echo planar k-space sampling (TR 2.15 s) and interleaved slice collection schemes were also compared against the 3D single shot trajectory at 2.2 s sTR. The quantified connectivity metrics included stationary spatial, time, and frequency domains, as well as dynamic analyses. Time domain methods included analyses of seed-based functional connectivity, regional homogeneity (ReHo), coefficient of variation, and spatial domain group level probabilistic independent component analysis (ICA). In frequency domain analyses, we examined fractional and amplitude of low frequency fluctuations. Aliasing effects were spatially and spectrally analyzed by comparing VLF (0.01–0.1 Hz), respiratory (0.12–0.35 Hz) and cardiac power (0.9–1.3 Hz) FFT maps at different sTRs. Quasi-periodic pattern (QPP) of VLF events were analyzed for effects on dynamic FC methods. The results in conventional time and spatial domain analyses remained virtually unchanged by the different sampling rates. In frequency domain, the aliasing occurred mainly in higher sTR (1–2 s) where cardiac power aliases over respiratory power. The VLF power maps suffered minimally from increasing sTRs. Interleaved data reconstruction induced lower ReHo compared to 3D sampling ( p < 0.001). Gradient recalled echo-planar imaging (EPI BOLD) data produced both better and worse metrics. In QPP analyses, the repeatability of the VLF pulse detection becomes linearly reduced with increasing sTR. In conclusion, the conventional resting state metrics (e.g., FC, ICA) were not markedly affected by different TRs (0.1–3 s). However, cardiorespiratory signals showed strongest aliasing in central brain regions in sTR 1–2 s. Pulsatile QPP and other dynamic analyses benefit linearly from short TR scanning.

The topic of investigating how mindfulness meditation training can have antidepressant effects via plastic changes in both resting state and meditation state brain activity is important in the rapidly emerging field of neuroplasticity. In the present study, we used a longitudinal design investigating resting state fMRI both before and after 40 days of meditation training in 13 novices. After training, we compared differences in network connectivity between rest and meditation using common resting state functional connectivity methods. Interregional methods were paired with local measures such as Regional Homogeneity. As expected, significant differences in functional connectivity both between states (rest versus meditation) and between time points (before versus after training) were observed. During meditation, the internal consistency in the precuneus and the temporoparietal junction increased, while the internal consistency of frontal brain regions decreased. A follow-up analysis of regional connectivity of the dorsal anterior cingulate cortex further revealed reduced connectivity with anterior insula during meditation. After meditation training, reduced resting state functional connectivity between the pregenual anterior cingulate and dorsal medical prefrontal cortex was observed. Most importantly, significantly reduced depression/anxiety scores were observed after training. Hence, these findings suggest that mindfulness meditation might be of therapeutic use by inducing plasticity related network changes altering the neuronal basis of affective disorders such as depression.

No abstract

Increasing neuroimaging evidence suggests that mindfulness meditation expertise is related to different functional and structural configurations of the default mode network (DMN), the salience network (SN) and the executive network at rest. However, longitudinal studies observing resting network plasticity effects in brains of novices who started to practice meditation are scarce and generally related to one dimension, such as structural or functional effects. The purpose of this study was to investigate structural and functional brain network changes (e.g. DMN) after 40 days of mindfulness meditation training in novices and set these in the context of potentially altered depression symptomatology and anxiety. We found overlapping structural and functional effects in precuneus, a posterior DMN region, where cortical thickness increased and low-frequency amplitudes (ALFF) decreased, while decreased ALFF in left precuneus/posterior cingulate cortex correlates with the reduction of (CES-D) depression scores. In conclusion, regional overlapping of structural and functional changes in precuneus may capture different components of the complex changes of mindfulness meditation training.

Neurobehavioral models of pedophilia and child sexual offending suggest a pattern of temporal and in particular prefrontal disturbances leading to inappropriate behavioral control and subsequently an increased propensity to sexually offend against children. However, clear empirical evidence for such mechanisms is still missing. Using a go/nogo paradigm in combination with functional magnetic resonance imaging (fMRI) we compared behavioral performance and neural response patterns among three groups of men matched for age and IQ: pedophiles with (N = 40) and without (N = 37) a history of hands-on sexual offences against children as well as healthy non-offending controls (N = 40). As compared to offending pedophiles, non-offending pedophiles exhibited superior inhibitory control as reflected by significantly lower rate of commission errors. Group-by-condition interaction analysis also revealed inhibition-related activation in the left posterior cingulate and the left superior frontal cortex that distinguished between offending and non-offending pedophiles, while no significant differences were found between pedophiles and healthy controls. Both areas showing distinct activation pattern among pedophiles play a critical role in linking neural networks that relate to effective cognitive functioning. Data therefore suggest that heightened inhibition-related recruitment of these areas as well as decreased amount of commission errors is related to better inhibitory control in pedophiles who successfully avoid committing hands-on sexual offences against children. Hum Brain Mapp 38:1092-1104, 2017. © 2016 Wiley Periodicals, Inc.

IntroductionFunctional magnetic resonance imaging (fMRI) combined with simultaneous electroencephalography (EEG‐fMRI) has become a major tool in mapping epilepsy sources. In the absence of detectable epileptiform activity, the resting state fMRI may still detect changes in the blood oxygen level‐dependent signal, suggesting intrinsic alterations in the underlying brain physiology.MethodsIn this study, we used coefficient of variation (CV) of critically sampled 10 Hz ultra‐fast fMRI (magnetoencephalography, MREG) signal to compare physiological variance between healthy controls (n = 10) and patients (n = 10) with drug‐resistant epilepsy (DRE).ResultsWe showed highly significant voxel‐level (p < 0.01, TFCE‐corrected) increase in the physiological variance in DRE patients. At individual level, the elevations range over three standard deviations (σ) above the control mean (μ) CVMREG values solely in DRE patients, enabling patient‐specific mapping of elevated physiological variance. The most apparent differences in group‐level analysis are found on white matter, brainstem, and cerebellum. Respiratory (0.12–0.4 Hz) and very‐low‐frequency (VLF = 0.009–0.1 Hz) signal variances were most affected.ConclusionsThe CVMREG increase was not explained by head motion or physiological cardiorespiratory activity, that is, it seems to be linked to intrinsic physiological pulsations. We suggest that intrinsic brain pulsations play a role in DRE and that critically sampled fMRI may provide a powerful tool for their identification.