Uncertainty in anticipation of uncomfortable rectal distension is modulated by the autonomic nervous system--a fMRI study in healthy volunteers.

The human brain responds both before and during the application of aversive stimuli. Anticipation allows the organism to prepare its nociceptive system to respond adequately to the subsequent stimulus. The context in which an uncomfortable stimulus is experienced may also influence neural processing. Uncertainty of occurrence, timing and intensity of an aversive event may lead to increased anticipatory anxiety, fear, physiological arousal and sensory perception. We aimed to identify, in healthy volunteers, the effects of uncertainty in the anticipation of uncomfortable rectal distension, and the impact of the autonomic nervous system (ANS) activity and anxiety-related psychological variables on neural mechanisms of anticipation of rectal distension using fMRI. Barostat-controlled uncomfortable rectal distensions were preceded by cued uncertain or certain anticipation in 15 healthy volunteers in a fMRI protocol at 3T. Electrocardiographic data were concurrently registered by MR scanner. The low frequency (LF)-component of the heart rate variability (HRV) time-series was extracted and inserted as a regressor in the fMRI model ('LF-HRV model'). The impact of ANS activity was analyzed by comparing the fMRI signal in the 'standard model' and in the 'LF-HRV model' across the different anticipation and distension conditions. The scores of the psychological questionnaires and the rating of perceived anticipatory anxiety were included as covariates in the fMRI data analysis. Our experiments led to the following key findings: 1) the subgenual anterior cingulate cortex (sgACC) is the only activation site that relates to uncertainty in healthy volunteers and is directly correlated to individual questionnaire score for pain-related anxiety; 2) uncertain anticipation of rectal distension involved several relevant brain regions, namely activation of sgACC and medial prefrontal cortex and deactivation of amygdala, insula, thalamus, secondary somatosensory cortex, supplementary motor area and cerebellum; 3) most of the brain activity during anticipation, but not distension, is associated with activity of the central autonomic network. This approach could be applied to study the ANS impact on brain activity in various pathological conditions, namely in patients with chronic digestive conditions characterized by visceral discomfort and ANS imbalance such as irritable bowel syndrome or inflammatory bowel diseases.

Residual convolutional autoencoder combined with a non-negative matrix factorization to estimate fetal heart rate.

The fetal heart rate (fHR) plays an important role in the determination of the good health of the fetus. Beside the traditional Doppler ultrasound technique, non-invasive fetal electrocardiography (fECG) has become an interesting alternative. However, extracting clean fECG from abdominal ECG (aECG) recordings is a challenging task due to the presence of the maternal ECG component and various noise sources. In this context, we propose a deep residual convolutional autoencoder network trained on synthetic aECG simulations followed by a transfer learning phase on real aECG recordings to extract the cleanest fECG. Afterwards, we propose to use a non-negative matrix factorization based approach on the obtained fECG to estimate the fHR. Our method is evaluated on three publicly available databases demonstrating that it can provide significant performance improvement against comparative methodologies. Clinical relevance- The presented method has the advantage of estimating the fetal heart rate from a single-channel abdominal electrocardiogram without prior knowledge on the noise sources nor the maternal R-peak locations.