Browsing by Department "Maastricht University"
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- Attention modulates the auditory cortical processing of spatial and category cues in naturalistic auditory scenes
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2016-06-07) Renvall, Hanna; Staeren, Noël; Barz, Claudia S.; Ley, Anke; Formisano, EliaThis combined fMRI and MEG study investigated brain activations during listening and attending to natural auditory scenes. We first recorded, using in-ear microphones, vocal non-speech sounds, and environmental sounds that were mixed to construct auditory scenes containing two concurrent sound streams. During the brain measurements, subjects attended to one of the streams while spatial acoustic information of the scene was either preserved (stereophonic sounds) or removed (monophonic sounds). Compared to monophonic sounds, stereophonic sounds evoked larger blood-oxygenation-level-dependent (BOLD) fMRI responses in the bilateral posterior superior temporal areas, independent of which stimulus attribute the subject was attending to. This finding is consistent with the functional role of these regions in the (automatic) processing of auditory spatial cues. Additionally, significant differences in the cortical activation patterns depending on the target of attention were observed. Bilateral planum temporale and inferior frontal gyrus were preferentially activated when attending to stereophonic environmental sounds, whereas when subjects attended to stereophonic voice sounds, the BOLD responses were larger at the bilateral middle superior temporal gyrus and sulcus, previously reported to show voice sensitivity. In contrast, the time-resolved MEG responses were stronger for mono- than stereophonic sounds in the bilateral auditory cortices at ~360 ms after the stimulus onset when attending to the voice excerpts within the combined sounds. The observed effects suggest that during the segregation of auditory objects from the auditory background, spatial sound cues together with other relevant temporal and spectral cues are processed in an attention-dependent manner at the cortical locations generally involved in sound recognition. More synchronous neuronal activation during monophonic than stereophonic sound processing, as well as (local) neuronal inhibitory mechanisms in the auditory cortex, may explain the simultaneous increase of BOLD responses and decrease of MEG responses. These findings highlight the complimentary role of electrophysiological and hemodynamic measures in addressing brain processing of complex stimuli. - Baseline gene expression in subcutaneous adipose tissue predicts diet-induced weight loss in individuals with obesity
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2023-03) Oghabian, Ali; van der Kolk, Birgitta W.; Marttinen, Pekka; Valsesia, Armand; Langin, Dominique; Saris, W. H.; Astrup, Arne; Blaak, Ellen E.; Pietiläinen, Kirsi H.Background: Weight loss effectively reduces cardiometabolic health risks among people with overweight and obesity, but inter-individual variability in weight loss maintenance is large. Here we studied whether baseline gene expression in subcutaneous adipose tissue predicts diet-induced weight loss success. Methods: Within the 8-month multicenter dietary intervention study DiOGenes, we classified a low weight-losers (low-WL) group and a high-WL group based on median weight loss percentage (9.9%) from 281 individuals. Using RNA sequencing, we identified the significantly differentially expressed genes between high-WL and low-WL at baseline and their enriched pathways. We used this information together with support vector machines with linear kernel to build classifier models that predict the weight loss classes. Results: Prediction models based on a selection of genes that are associated with the discovered pathways ‘lipid metabolism’ (max AUC = 0.74, 95% CI [0.62–0.86]) and ‘response to virus’ (max AUC = 0.72,95% CI [0.61–0.83]) predicted the weight-loss classes high-WL/low-WL significantly better than models based on randomly selected genes (P < 0.01). The performance of the models based on ‘response to virus’ genes is highly dependent on those genes that are also associated with lipid metabolism. Incorporation of baseline clinical factors into these models did not noticeably enhance the model performance in most of the runs. This study demonstrates that baseline adipose tissue gene expression data, together with supervised machine learning, facilitates the characterization of the determinants of successful weight loss. - An Interdisciplinary View of Marketing Ethics
A3 Kirjan tai muun kokoomateoksen osa(2020) Mahr, Dominik; Caic, Martina; Odekerken-Schröder, Gaby